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ontologies</title> <meta name="description" content="Search results for: medical ontologies"> <meta name="keywords" content="medical ontologies"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="medical ontologies"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 3471</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: medical ontologies</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3471</span> Proposition of an Ontology of Diseases and Their Signs from Medical Ontologies Integration</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Adama%20Sow">Adama Sow</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdoulaye%20Guiss%C2%B4e"> Abdoulaye Guiss´e</a>, <a href="https://publications.waset.org/abstracts/search?q=Oumar%20Niang"> Oumar Niang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> To assist medical diagnosis, we propose a federation of several existing and open medical ontologies and terminologies. The goal is to merge the strengths of all these resources to provide clinicians the access to a variety of shared knowledges that can facilitate identification and association of human diseases and all of their available characteristic signs such as symptoms and clinical signs. This work results to an integration model loaded from target known ontologies of the bioportal platform such as DOID, MESH, and SNOMED for diseases selection, SYMP, and CSSO for all existing signs. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=medical%20decision" title="medical decision">medical decision</a>, <a href="https://publications.waset.org/abstracts/search?q=medical%20ontologies" title=" medical ontologies"> medical ontologies</a>, <a href="https://publications.waset.org/abstracts/search?q=ontologies%20integration" title=" ontologies integration"> ontologies integration</a>, <a href="https://publications.waset.org/abstracts/search?q=linked%20data" title=" linked data"> linked data</a>, <a href="https://publications.waset.org/abstracts/search?q=knowledge%20engineering" title=" knowledge engineering"> knowledge engineering</a>, <a href="https://publications.waset.org/abstracts/search?q=e-health%20system" title=" e-health system"> e-health system</a> </p> <a href="https://publications.waset.org/abstracts/93508/proposition-of-an-ontology-of-diseases-and-their-signs-from-medical-ontologies-integration" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/93508.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">197</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3470</span> Resources-Based Ontology Matching to Access Learning Resources</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20Elbyed">A. Elbyed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Nowadays, ontologies are used for achieving a common understanding within a user community and for sharing domain knowledge. However, the de-centralized nature of the web makes indeed inevitable that small communities will use their own ontologies to describe their data and to index their own resources. Certainly, accessing to resources from various ontologies created independently is an important challenge for answering end user queries. Ontology mapping is thus required for combining ontologies. However, mapping complete ontologies at run time is a computationally expensive task. This paper proposes a system in which mappings between concepts may be generated dynamically as the concepts are encountered during user queries. In this way, the interaction itself defines the context in which small and relevant portions of ontologies are mapped. We illustrate application of the proposed system in the context of Technology Enhanced Learning (TEL) where learners need to access to learning resources covering specific concepts. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=resources%20query" title="resources query">resources query</a>, <a href="https://publications.waset.org/abstracts/search?q=ontologies" title=" ontologies"> ontologies</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology%20mapping" title=" ontology mapping"> ontology mapping</a>, <a href="https://publications.waset.org/abstracts/search?q=similarity%20measures" title=" similarity measures"> similarity measures</a>, <a href="https://publications.waset.org/abstracts/search?q=semantic%20web" title=" semantic web"> semantic web</a>, <a href="https://publications.waset.org/abstracts/search?q=e-learning" title=" e-learning"> e-learning</a> </p> <a href="https://publications.waset.org/abstracts/43305/resources-based-ontology-matching-to-access-learning-resources" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/43305.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">312</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3469</span> Consolidating Service Engineering Ontologies Building Service Ontology from SOA Modeling Language (SoaML)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Purnomo%20Yustianto">Purnomo Yustianto</a>, <a href="https://publications.waset.org/abstracts/search?q=Robin%20Doss"> Robin Doss</a>, <a href="https://publications.waset.org/abstracts/search?q=Suhardi"> Suhardi</a>, <a href="https://publications.waset.org/abstracts/search?q=Novianto%20Budi%20Kurniawan"> Novianto Budi Kurniawan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As a term for characterizing a process of devising a service system, the term ‘service engineering’ is still regarded as an ‘open’ research challenge due to unspecified details and conflicting perspectives. This paper presents consolidated service engineering ontologies in collecting, specifying and defining relationship between components pertinent within the context of service engineering. The ontologies are built by way of literature surveys from the collected conceptual works by collating various concepts into an integrated ontology. Two ontologies are produced: general service ontology and software service ontology. The software-service ontology is drawn from the informatics domain, while the generalized ontology of a service system is built from both a business management and the information system perspective. The produced ontologies are verified by exercising conceptual operationalizations of the ontologies in adopting several service orientation features and service system patterns. The proposed ontologies are demonstrated to be sufficient to serve as a basis for a service engineering framework. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=engineering" title="engineering">engineering</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology" title=" ontology"> ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=service" title=" service"> service</a>, <a href="https://publications.waset.org/abstracts/search?q=SoaML" title=" SoaML"> SoaML</a> </p> <a href="https://publications.waset.org/abstracts/98182/consolidating-service-engineering-ontologies-building-service-ontology-from-soa-modeling-language-soaml" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/98182.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">188</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3468</span> A Validation Technique for Integrated Ontologies</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Neli%20P.%20Zlatareva">Neli P. Zlatareva</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Ontology validation is an important part of web applications’ development, where knowledge integration and ontological reasoning play a fundamental role. It aims to ensure the consistency and correctness of ontological knowledge and to guarantee that ontological reasoning is carried out in a meaningful way. Existing approaches to ontology validation address more or less specific validation issues, but the overall process of validating web ontologies has not been formally established yet. As the size and the number of web ontologies continue to grow, the necessity to validate and ensure their consistency and interoperability is becoming increasingly important. This paper presents a validation technique intended to test the consistency of independent ontologies utilized by a common application. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=knowledge%20engineering" title="knowledge engineering">knowledge engineering</a>, <a href="https://publications.waset.org/abstracts/search?q=ontological%20reasoning" title=" ontological reasoning"> ontological reasoning</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology%20validation" title=" ontology validation"> ontology validation</a>, <a href="https://publications.waset.org/abstracts/search?q=semantic%20web" title=" semantic web"> semantic web</a> </p> <a href="https://publications.waset.org/abstracts/26959/a-validation-technique-for-integrated-ontologies" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/26959.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">322</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3467</span> Parallel Querying of Distributed Ontologies with Shared Vocabulary</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sharjeel%20Aslam">Sharjeel Aslam</a>, <a href="https://publications.waset.org/abstracts/search?q=Vassil%20Vassilev"> Vassil Vassilev</a>, <a href="https://publications.waset.org/abstracts/search?q=Karim%20Ouazzane"> Karim Ouazzane</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Ontologies and various semantic repositories became a convenient approach for implementing model-driven architectures of distributed systems on the Web. SPARQL is the standard query language for querying such. However, although SPARQL is well-established standard for querying semantic repositories in RDF and OWL format and there are commonly used APIs which supports it, like Jena for Java, its parallel option is not incorporated in them. This article presents a complete framework consisting of an object algebra for parallel RDF and an index-based implementation of the parallel query engine capable of dealing with the distributed RDF ontologies which share common vocabulary. It has been implemented in Java, and for validation of the algorithms has been applied to the problem of organizing virtual exhibitions on the Web. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=distributed%20ontologies" title="distributed ontologies">distributed ontologies</a>, <a href="https://publications.waset.org/abstracts/search?q=parallel%20querying" title=" parallel querying"> parallel querying</a>, <a href="https://publications.waset.org/abstracts/search?q=semantic%20indexing" title=" semantic indexing"> semantic indexing</a>, <a href="https://publications.waset.org/abstracts/search?q=shared%20vocabulary" title=" shared vocabulary"> shared vocabulary</a>, <a href="https://publications.waset.org/abstracts/search?q=SPARQL" title=" SPARQL"> SPARQL</a> </p> <a href="https://publications.waset.org/abstracts/105046/parallel-querying-of-distributed-ontologies-with-shared-vocabulary" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/105046.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">204</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3466</span> Combining Instance-Based and Reasoning-Based Approaches for Ontology Matching</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abderrahmane%20Khiat">Abderrahmane Khiat</a>, <a href="https://publications.waset.org/abstracts/search?q=Moussa%20Benaissa"> Moussa Benaissa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Due to the increasing number of sources of information available on the web and their distribution and heterogeneity, ontology alignment became a very important and inevitable problem to ensure semantic interoperability. Instance-based ontology alignment is based on the comparison of the extensions of concepts; and represents a very promising technique to find semantic correspondences between entities of different ontologies. In practice, two situations may arise: ontologies that share many common instances and ontologies that share few or do not share common instances. In this paper, we describe an approach to manage the latter case. This approach exploits the reasoning on ontologies in order to create a corpus of common instances. We show that it is theoretically powerful because it is based on description logics and very useful in practice. We present the experimental results obtained by running our approach on ontologies of OAEI 2012 benchmark test. The results show the performance of our approach. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=description%20logic%20inference" title="description logic inference">description logic inference</a>, <a href="https://publications.waset.org/abstracts/search?q=instance-based%20ontology%20alignment" title=" instance-based ontology alignment"> instance-based ontology alignment</a>, <a href="https://publications.waset.org/abstracts/search?q=semantic%20interoperability" title=" semantic interoperability"> semantic interoperability</a>, <a href="https://publications.waset.org/abstracts/search?q=semantic%20web" title=" semantic web"> semantic web</a> </p> <a href="https://publications.waset.org/abstracts/6254/combining-instance-based-and-reasoning-based-approaches-for-ontology-matching" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6254.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">447</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3465</span> An Approach to Integrate Ontologies of Open Educational Resources in Knowledge Base Management Systems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Firas%20A.%20Al%20Laban">Firas A. Al Laban</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Chabi"> Mohamed Chabi</a>, <a href="https://publications.waset.org/abstracts/search?q=Sammani%20Danwawu%20Abdullahi"> Sammani Danwawu Abdullahi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> There are a real needs to integrate types of Open Educational Resources (OER) with an intelligent system to extract information and knowledge in the semantic searching level. Those needs raised because most of current learning standard adopted web based learning and the e-learning systems does not always serve all educational goals. Semantic Web systems provide educators, students, and researchers with intelligent queries based on a semantic knowledge management learning system. An ontology-based learning system is an advanced system, where ontology plays the core of the semantic web in a smart learning environment. The objective of this paper is to discuss the potentials of ontologies and mapping different kinds of ontologies; heterogeneous or homogenous to manage and control different types of Open Educational Resources. The important contribution of this research is to approach a methodology uses logical rules and conceptual relations to map between ontologies of different educational resources. We expect from this methodology to establish for an intelligent educational system supporting student tutoring, self and lifelong learning system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=knowledge%20management%20systems" title="knowledge management systems">knowledge management systems</a>, <a href="https://publications.waset.org/abstracts/search?q=ontologies" title=" ontologies"> ontologies</a>, <a href="https://publications.waset.org/abstracts/search?q=semantic%20web" title=" semantic web"> semantic web</a>, <a href="https://publications.waset.org/abstracts/search?q=open%20educational%20resources" title=" open educational resources "> open educational resources </a> </p> <a href="https://publications.waset.org/abstracts/27021/an-approach-to-integrate-ontologies-of-open-educational-resources-in-knowledge-base-management-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/27021.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">498</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3464</span> Reverse Logistics Information Management Using Ontological Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=F.%20Lhafiane">F. Lhafiane</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Elbyed"> A. Elbyed</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Bouchoum"> M. Bouchoum</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Reverse Logistics (RL) Process is considered as complex and dynamic network that involves many stakeholders such as: suppliers, manufactures, warehouse, retails, and costumers, this complexity is inherent in such process due to lack of perfect knowledge or conflicting information. Ontologies, on the other hand, can be considered as an approach to overcome the problem of sharing knowledge and communication among the various reverse logistics partners. In this paper, we propose a semantic representation based on hybrid architecture for building the Ontologies in an ascendant way, this method facilitates the semantic reconciliation between the heterogeneous information systems (ICT) that support reverse logistics Processes and product data. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Reverse%20Logistics" title="Reverse Logistics">Reverse Logistics</a>, <a href="https://publications.waset.org/abstracts/search?q=information%20management" title=" information management"> information management</a>, <a href="https://publications.waset.org/abstracts/search?q=heterogeneity" title=" heterogeneity"> heterogeneity</a>, <a href="https://publications.waset.org/abstracts/search?q=ontologies" title=" ontologies"> ontologies</a>, <a href="https://publications.waset.org/abstracts/search?q=semantic%20web" title=" semantic web"> semantic web</a> </p> <a href="https://publications.waset.org/abstracts/23720/reverse-logistics-information-management-using-ontological-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/23720.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">492</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3463</span> Merging and Comparing Ontologies Generically</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Xiuzhan%20Guo">Xiuzhan Guo</a>, <a href="https://publications.waset.org/abstracts/search?q=Arthur%20Berrill"> Arthur Berrill</a>, <a href="https://publications.waset.org/abstracts/search?q=Ajinkya%20Kulkarni"> Ajinkya Kulkarni</a>, <a href="https://publications.waset.org/abstracts/search?q=Kostya%20Belezko"> Kostya Belezko</a>, <a href="https://publications.waset.org/abstracts/search?q=Min%20Luo"> Min Luo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Ontology operations, e.g., aligning and merging, were studied and implemented extensively in different settings, such as categorical operations, relation algebras, and typed graph grammars, with different concerns. However, aligning and merging operations in the settings share some generic properties, e.g., idempotence, commutativity, associativity, and representativity, labeled by (I), (C), (A), and (R), respectively, which are defined on an ontology merging system (D~M), where D is a non-empty set of the ontologies concerned, ~ is a binary relation on D modeling ontology aligning and M is a partial binary operation on D modeling ontology merging. Given an ontology repository, a finite set O ⊆ D, its merging closure Ô is the smallest set of ontologies, which contains the repository and is closed with respect to merging. If (I), (C), (A), and (R) are satisfied, then both D and Ô are partially ordered naturally by merging, Ô is finite and can be computed, compared, and sorted efficiently, including sorting, selecting, and querying some specific elements, e.g., maximal ontologies and minimal ontologies. We also show that the ontology merging system, given by ontology V -alignment pairs and pushouts, satisfies the properties: (I), (C), (A), and (R) so that the merging system is partially ordered and the merging closure of a given repository with respect to pushouts can be computed efficiently. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ontology%20aligning" title="ontology aligning">ontology aligning</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology%20merging" title=" ontology merging"> ontology merging</a>, <a href="https://publications.waset.org/abstracts/search?q=merging%20system" title=" merging system"> merging system</a>, <a href="https://publications.waset.org/abstracts/search?q=poset" title=" poset"> poset</a>, <a href="https://publications.waset.org/abstracts/search?q=merging%20closure" title=" merging closure"> merging closure</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology%20V-alignment%20pair" title=" ontology V-alignment pair"> ontology V-alignment pair</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology%20homomorphism" title=" ontology homomorphism"> ontology homomorphism</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology%20V-alignment%20pair%20homomorphism" title=" ontology V-alignment pair homomorphism"> ontology V-alignment pair homomorphism</a>, <a href="https://publications.waset.org/abstracts/search?q=pushout" title=" pushout"> pushout</a> </p> <a href="https://publications.waset.org/abstracts/155767/merging-and-comparing-ontologies-generically" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/155767.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">893</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3462</span> Application of Ontologies to Contract for Difference Documents</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Renato%20Figueira%20Franco">Renato Figueira Franco</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper aims to create a representational information system applied to the securities market, particularly the development of an ontology applied to the analysis of the Key Information Documents of Contracts for Difference. The process of obtaining knowledge and its proper formal representation has raised the attention both from the scientific literature and the capital markets supervisory authorities. The formal knowledge representation is embodied in the construction of ontologies, which are responsible for defining a knowledge base structure of a given scientific domain, facilitating its understanding, and allowing its sharing among the scientific community. The scope of this study is restricted to the analysis of capital markets ontologies in order to capture its structure, semantics and knowledge sharing between people and systems. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ontology" title="ontology">ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=financial%20markets" title=" financial markets"> financial markets</a>, <a href="https://publications.waset.org/abstracts/search?q=CFD" title=" CFD"> CFD</a>, <a href="https://publications.waset.org/abstracts/search?q=PRIIPs" title=" PRIIPs"> PRIIPs</a>, <a href="https://publications.waset.org/abstracts/search?q=key%20information%20documents" title=" key information documents"> key information documents</a> </p> <a href="https://publications.waset.org/abstracts/174001/application-of-ontologies-to-contract-for-difference-documents" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/174001.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">66</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3461</span> Ontologies for Social Media Digital Evidence</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Edlira%20Kalemi">Edlira Kalemi</a>, <a href="https://publications.waset.org/abstracts/search?q=Sule%20Yildirim-Yayilgan"> Sule Yildirim-Yayilgan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Online Social Networks (OSNs) are nowadays being used widely and intensively for crime investigation and prevention activities. As they provide a lot of information they are used by the law enforcement and intelligence. An extensive review on existing solutions and models for collecting intelligence from this source of information and making use of it for solving crimes has been presented in this article. The main focus is on smart solutions and models where ontologies have been used as the main approach for representing criminal domain knowledge. A framework for a prototype ontology named SC-Ont will be described. This defines terms of the criminal domain ontology and the relations between them. The terms and the relations are extracted during both this review and the discussions carried out with domain experts. The development of SC-Ont is still ongoing work, where in this paper, we report mainly on the motivation for using smart ontology models and the possible benefits of using them for solving crimes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=criminal%20digital%20evidence" title="criminal digital evidence">criminal digital evidence</a>, <a href="https://publications.waset.org/abstracts/search?q=social%20media" title=" social media"> social media</a>, <a href="https://publications.waset.org/abstracts/search?q=ontologies" title=" ontologies"> ontologies</a>, <a href="https://publications.waset.org/abstracts/search?q=reasoning" title=" reasoning"> reasoning</a> </p> <a href="https://publications.waset.org/abstracts/41165/ontologies-for-social-media-digital-evidence" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41165.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">388</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3460</span> A Collaborative Platform for Multilingual Ontology Development</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ahmed%20Tawfik">Ahmed Tawfik</a>, <a href="https://publications.waset.org/abstracts/search?q=Fausto%20Giunchiglia"> Fausto Giunchiglia</a>, <a href="https://publications.waset.org/abstracts/search?q=Vincenzo%20Maltese"> Vincenzo Maltese</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Ontologies provide a common understanding of a specific domain of interest that can be communicated between people and used as background knowledge for automated reasoning in a wide range of applications. In this paper we address the design of multilingual ontologies following well-defined knowledge engineering methodologies with the support of novel collaborative development approaches. In particular, we present a collaborative platform which allows ontologies to be developed incrementally in multiple languages. This is made possible via an appropriate mapping between language independent concepts and one lexicalization per language (or a lexical gap in case such lexicalization does not exist). The collaborative platform has been designed to support the development of the Universal Knowledge Core, a multilingual ontology currently in English, Italian, Chinese, Mongolian, Hindi, and Bangladeshi. Its design follows a workflow-based development methodology that models resources as a set of collaborative objects and assigns customizable workflows to build and maintain each collaborative object in a community driven manner, with extensive support of modern web 2.0 social and collaborative features. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=knowledge%20diversity" title="knowledge diversity">knowledge diversity</a>, <a href="https://publications.waset.org/abstracts/search?q=knowledge%20representation" title=" knowledge representation"> knowledge representation</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology" title=" ontology"> ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=development" title=" development"> development</a> </p> <a href="https://publications.waset.org/abstracts/18521/a-collaborative-platform-for-multilingual-ontology-development" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18521.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">392</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3459</span> Pushing the Boundary of Parallel Tractability for Ontology Materialization via Boolean Circuits</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zhangquan%20Zhou">Zhangquan Zhou</a>, <a href="https://publications.waset.org/abstracts/search?q=Guilin%20Qi"> Guilin Qi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Materialization is an important reasoning service for applications built on the Web Ontology Language (OWL). To make materialization efficient in practice, current research focuses on deciding tractability of an ontology language and designing parallel reasoning algorithms. However, some well-known large-scale ontologies, such as YAGO, have been shown to have good performance for parallel reasoning, but they are expressed in ontology languages that are not parallelly tractable, i.e., the reasoning is inherently sequential in the worst case. This motivates us to study the problem of parallel tractability of ontology materialization from a theoretical perspective. That is we aim to identify the ontologies for which materialization is parallelly tractable, i.e., in the NC complexity. Since the NC complexity is defined based on Boolean circuit that is widely used to investigate parallel computing problems, we first transform the problem of materialization to evaluation of Boolean circuits, and then study the problem of parallel tractability based on circuits. In this work, we focus on datalog rewritable ontology languages. We use Boolean circuits to identify two classes of datalog rewritable ontologies (called parallelly tractable classes) such that materialization over them is parallelly tractable. We further investigate the parallel tractability of materialization of a datalog rewritable OWL fragment DHL (Description Horn Logic). Based on the above results, we analyze real-world datasets and show that many ontologies expressed in DHL belong to the parallelly tractable classes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ontology%20materialization" title="ontology materialization">ontology materialization</a>, <a href="https://publications.waset.org/abstracts/search?q=parallel%20reasoning" title=" parallel reasoning"> parallel reasoning</a>, <a href="https://publications.waset.org/abstracts/search?q=datalog" title=" datalog"> datalog</a>, <a href="https://publications.waset.org/abstracts/search?q=Boolean%20circuit" title=" Boolean circuit"> Boolean circuit</a> </p> <a href="https://publications.waset.org/abstracts/57402/pushing-the-boundary-of-parallel-tractability-for-ontology-materialization-via-boolean-circuits" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/57402.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">271</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3458</span> Arabic Quran Search Tool Based on Ontology</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Alqahtani">Mohammad Alqahtani</a>, <a href="https://publications.waset.org/abstracts/search?q=Eric%20Atwell"> Eric Atwell</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper reviews and classifies most of the important types of search techniques that have been applied on the holy Quran. Then, it addresses the limitations in these techniques. Additionally, this paper surveys most existing Quranic ontologies and what are their deficiencies. Finally, it explains a new search tool called: A semantic search tool for Al Quran based on Qur’anic ontologies. This tool will overcome all limitations in the existing Quranic search applications. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=holy%20Quran" title="holy Quran">holy Quran</a>, <a href="https://publications.waset.org/abstracts/search?q=natural%20language%20processing%20%28NLP%29" title=" natural language processing (NLP)"> natural language processing (NLP)</a>, <a href="https://publications.waset.org/abstracts/search?q=semantic%20search" title=" semantic search"> semantic search</a>, <a href="https://publications.waset.org/abstracts/search?q=information%20retrieval%20%28IR%29" title=" information retrieval (IR)"> information retrieval (IR)</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology" title=" ontology"> ontology</a> </p> <a href="https://publications.waset.org/abstracts/31315/arabic-quran-search-tool-based-on-ontology" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31315.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">572</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3457</span> A Temporal QoS Ontology For ERTMS/ETCS</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Marc%20Sango">Marc Sango</a>, <a href="https://publications.waset.org/abstracts/search?q=Olimpia%20Hoinaru"> Olimpia Hoinaru</a>, <a href="https://publications.waset.org/abstracts/search?q=Christophe%20Gransart"> Christophe Gransart</a>, <a href="https://publications.waset.org/abstracts/search?q=Laurence%20Duchien"> Laurence Duchien</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Ontologies offer a means for representing and sharing information in many domains, particularly in complex domains. For example, it can be used for representing and sharing information of System Requirement Specification (SRS) of complex systems like the SRS of ERTMS/ETCS written in natural language. Since this system is a real-time and critical system, generic ontologies, such as OWL and generic ERTMS ontologies provide minimal support for modeling temporal information omnipresent in these SRS documents. To support the modeling of temporal information, one of the challenges is to enable representation of dynamic features evolving in time within a generic ontology with a minimal redesign of it. The separation of temporal information from other information can help to predict system runtime operation and to properly design and implement them. In addition, it is helpful to provide a reasoning and querying techniques to reason and query temporal information represented in the ontology in order to detect potential temporal inconsistencies. Indeed, a user operation, such as adding a new constraint on existing planning constraints can cause temporal inconsistencies, which can lead to system failures. To address this challenge, we propose a lightweight 3-layer temporal Quality of Service (QoS) ontology for representing, reasoning and querying over temporal and non-temporal information in a complex domain ontology. Representing QoS entities in separated layers can clarify the distinction between the non QoS entities and the QoS entities in an ontology. The upper generic layer of the proposed ontology provides an intuitive knowledge of domain components, specially ERTMS/ETCS components. The separation of the intermediate QoS layer from the lower QoS layer allows us to focus on specific QoS Characteristics, such as temporal or integrity characteristics. In this paper, we focus on temporal information that can be used to predict system runtime operation. To evaluate our approach, an example of the proposed domain ontology for handover operation, as well as a reasoning rule over temporal relations in this domain-specific ontology, are given. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=system%20requirement%20specification" title="system requirement specification">system requirement specification</a>, <a href="https://publications.waset.org/abstracts/search?q=ERTMS%2FETCS" title=" ERTMS/ETCS"> ERTMS/ETCS</a>, <a href="https://publications.waset.org/abstracts/search?q=temporal%20ontologies" title=" temporal ontologies"> temporal ontologies</a>, <a href="https://publications.waset.org/abstracts/search?q=domain%20ontologies" title=" domain ontologies"> domain ontologies</a> </p> <a href="https://publications.waset.org/abstracts/20625/a-temporal-qos-ontology-for-ertmsetcs" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20625.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">422</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3456</span> Application of Directed Acyclic Graphs for Threat Identification Based on Ontologies</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Arun%20Prabhakar">Arun Prabhakar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Threat modeling is an important activity carried out in the initial stages of the development lifecycle that helps in building proactive security measures in the product. Though there are many techniques and tools available today, one of the common challenges with the traditional methods is the lack of a systematic approach in identifying security threats. The proposed solution describes an organized model by defining ontologies that help in building patterns to enumerate threats. The concepts of graph theory are applied to build the pattern for discovering threats for any given scenario. This graph-based solution also brings in other benefits, making it a customizable and scalable model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=directed%20acyclic%20graph" title="directed acyclic graph">directed acyclic graph</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology" title=" ontology"> ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=patterns" title=" patterns"> patterns</a>, <a href="https://publications.waset.org/abstracts/search?q=threat%20identification" title=" threat identification"> threat identification</a>, <a href="https://publications.waset.org/abstracts/search?q=threat%20modeling" title=" threat modeling"> threat modeling</a> </p> <a href="https://publications.waset.org/abstracts/132007/application-of-directed-acyclic-graphs-for-threat-identification-based-on-ontologies" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/132007.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">139</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3455</span> Ontology Mapping with R-GNN for IT Infrastructure: Enhancing Ontology Construction and Knowledge Graph Expansion</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Andrey%20Khalov">Andrey Khalov</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The rapid growth of unstructured data necessitates advanced methods for transforming raw information into structured knowledge, particularly in domain-specific contexts such as IT service management and outsourcing. This paper presents a methodology for automatically constructing domain ontologies using the DOLCE framework as the base ontology. The research focuses on expanding ITIL-based ontologies by integrating concepts from ITSMO, followed by the extraction of entities and relationships from domain-specific texts through transformers and statistical methods like formal concept analysis (FCA). In particular, this work introduces an R-GNN-based approach for ontology mapping, enabling more efficient entity extraction and ontology alignment with existing knowledge bases. Additionally, the research explores transfer learning techniques using pre-trained transformer models (e.g., DeBERTa-v3-large) fine-tuned on synthetic datasets generated via large language models such as LLaMA. The resulting ontology, termed IT Ontology (ITO), is evaluated against existing methodologies, highlighting significant improvements in precision and recall. This study advances the field of ontology engineering by automating the extraction, expansion, and refinement of ontologies tailored to the IT domain, thus bridging the gap between unstructured data and actionable knowledge. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ontology%20mapping" title="ontology mapping">ontology mapping</a>, <a href="https://publications.waset.org/abstracts/search?q=knowledge%20graphs" title=" knowledge graphs"> knowledge graphs</a>, <a href="https://publications.waset.org/abstracts/search?q=R-GNN" title=" R-GNN"> R-GNN</a>, <a href="https://publications.waset.org/abstracts/search?q=ITIL" title=" ITIL"> ITIL</a>, <a href="https://publications.waset.org/abstracts/search?q=NER" title=" NER"> NER</a> </p> <a href="https://publications.waset.org/abstracts/192575/ontology-mapping-with-r-gnn-for-it-infrastructure-enhancing-ontology-construction-and-knowledge-graph-expansion" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/192575.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">15</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3454</span> A Novel Framework for User-Friendly Ontology-Mediated Access to Relational Databases</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Efthymios%20Chondrogiannis">Efthymios Chondrogiannis</a>, <a href="https://publications.waset.org/abstracts/search?q=Vassiliki%20Andronikou"> Vassiliki Andronikou</a>, <a href="https://publications.waset.org/abstracts/search?q=Efstathios%20Karanastasis"> Efstathios Karanastasis</a>, <a href="https://publications.waset.org/abstracts/search?q=Theodora%20Varvarigou"> Theodora Varvarigou</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A large amount of data is typically stored in relational databases (DB). The latter can efficiently handle user queries which intend to elicit the appropriate information from data sources. However, direct access and use of this data requires the end users to have an adequate technical background, while they should also cope with the internal data structure and values presented. Consequently the information retrieval is a quite difficult process even for IT or DB experts, taking into account the limited contributions of relational databases from the conceptual point of view. Ontologies enable users to formally describe a domain of knowledge in terms of concepts and relations among them and hence they can be used for unambiguously specifying the information captured by the relational database. However, accessing information residing in a database using ontologies is feasible, provided that the users are keen on using semantic web technologies. For enabling users form different disciplines to retrieve the appropriate data, the design of a Graphical User Interface is necessary. In this work, we will present an interactive, ontology-based, semantically enable web tool that can be used for information retrieval purposes. The tool is totally based on the ontological representation of underlying database schema while it provides a user friendly environment through which the users can graphically form and execute their queries. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ontologies" title="ontologies">ontologies</a>, <a href="https://publications.waset.org/abstracts/search?q=relational%20databases" title=" relational databases"> relational databases</a>, <a href="https://publications.waset.org/abstracts/search?q=SPARQL" title=" SPARQL"> SPARQL</a>, <a href="https://publications.waset.org/abstracts/search?q=web%20interface" title=" web interface"> web interface</a> </p> <a href="https://publications.waset.org/abstracts/21795/a-novel-framework-for-user-friendly-ontology-mediated-access-to-relational-databases" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21795.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">272</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3453</span> INCIPIT-CRIS: A Research Information System Combining Linked Data Ontologies and Persistent Identifiers</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=David%20Nogueiras%20Blanco">David Nogueiras Blanco</a>, <a href="https://publications.waset.org/abstracts/search?q=Amir%20Alwash"> Amir Alwash</a>, <a href="https://publications.waset.org/abstracts/search?q=Arnaud%20Gaudinat"> Arnaud Gaudinat</a>, <a href="https://publications.waset.org/abstracts/search?q=Ren%C3%A9%20Schneider"> René Schneider</a> </p> <p class="card-text"><strong>Abstract:</strong></p> At a time when the access to and the sharing of information are crucial in the world of research, the use of technologies such as persistent identifiers (PIDs), Current Research Information Systems (CRIS), and ontologies may create platforms for information sharing if they respond to the need of disambiguation of their data by assuring interoperability inside and between other systems. INCIPIT-CRIS is a continuation of the former INCIPIT project, whose goal was to set up an infrastructure for a low-cost attribution of PIDs with high granularity based on Archival Resource Keys (ARKs). INCIPIT-CRIS can be interpreted as a logical consequence and propose a research information management system developed from scratch. The system has been created on and around the Schema.org ontology with a further articulation of the use of ARKs. It is thus built upon the infrastructure previously implemented (i.e., INCIPIT) in order to enhance the persistence of URIs. As a consequence, INCIPIT-CRIS aims to be the hinge between previously separated aspects such as CRIS, ontologies and PIDs in order to produce a powerful system allowing the resolution of disambiguation problems using a combination of an ontology such as Schema.org and unique persistent identifiers such as ARK, allowing the sharing of information through a dedicated platform, but also the interoperability of the system by representing the entirety of the data as RDF triplets. This paper aims to present the implemented solution as well as its simulation in real life. We will describe the underlying ideas and inspirations while going through the logic and the different functionalities implemented and their links with ARKs and Schema.org. Finally, we will discuss the tests performed with our project partner, the Swiss Institute of Bioinformatics (SIB), by the use of large and real-world data sets. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=current%20research%20information%20systems" title="current research information systems">current research information systems</a>, <a href="https://publications.waset.org/abstracts/search?q=linked%20data" title=" linked data"> linked data</a>, <a href="https://publications.waset.org/abstracts/search?q=ontologies" title=" ontologies"> ontologies</a>, <a href="https://publications.waset.org/abstracts/search?q=persistent%20identifier" title=" persistent identifier"> persistent identifier</a>, <a href="https://publications.waset.org/abstracts/search?q=schema.org" title=" schema.org"> schema.org</a>, <a href="https://publications.waset.org/abstracts/search?q=semantic%20web" title="semantic web">semantic web</a> </p> <a href="https://publications.waset.org/abstracts/152059/incipit-cris-a-research-information-system-combining-linked-data-ontologies-and-persistent-identifiers" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/152059.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">135</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3452</span> Knowledge Elicitation Approach for Formal Ontology Design: An Exploratory Study Applied in Industry for Knowledge Management</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ouassila%20Labbani-Narsis">Ouassila Labbani-Narsis</a>, <a href="https://publications.waset.org/abstracts/search?q=Christophe%20Nicolle"> Christophe Nicolle</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Building formal ontologies remains a complex process for companies. In the literature, this process is based on the technical knowledge and expertise of domain experts, without further details on the used methodologies. Possible problems of disagreements between experts, expression of tacit knowledge related to high level know-how rarely verbalized, qualification of results by using cases, or simply adhesion of the group of experts, remain currently unsolved. This paper proposes a methodological approach based on knowledge elicitation for the conception of formal, consensual, and shared ontologies. The proposed approach is experimentally tested on industrial collaboration projects in the field of manufacturing (associating knowledge sources from multinational companies) and in the field of viticulture (associating explicit knowledge and implicit knowledge acquired through observation). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=collaborative%20ontology%20engineering" title="collaborative ontology engineering">collaborative ontology engineering</a>, <a href="https://publications.waset.org/abstracts/search?q=knowledge%20elicitation" title=" knowledge elicitation"> knowledge elicitation</a>, <a href="https://publications.waset.org/abstracts/search?q=knowledge%20engineering" title=" knowledge engineering"> knowledge engineering</a>, <a href="https://publications.waset.org/abstracts/search?q=knowledge%20management" title=" knowledge management"> knowledge management</a> </p> <a href="https://publications.waset.org/abstracts/160107/knowledge-elicitation-approach-for-formal-ontology-design-an-exploratory-study-applied-in-industry-for-knowledge-management" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/160107.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">78</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3451</span> Design of a Pneumonia Ontology for Diagnosis Decision Support System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sabrina%20Azzi">Sabrina Azzi</a>, <a href="https://publications.waset.org/abstracts/search?q=Michal%20Iglewski"> Michal Iglewski</a>, <a href="https://publications.waset.org/abstracts/search?q=V%C3%A9ronique%20Nabelsi"> Véronique Nabelsi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Diagnosis error problem is frequent and one of the most important safety problems today. One of the main objectives of our work is to propose an ontological representation that takes into account the diagnostic criteria in order to improve the diagnostic. We choose pneumonia disease since it is one of the frequent diseases affected by diagnosis errors and have harmful effects on patients. To achieve our aim, we use a semi-automated method to integrate diverse knowledge sources that include publically available pneumonia disease guidelines from international repositories, biomedical ontologies and electronic health records. We follow the principles of the Open Biomedical Ontologies (OBO) Foundry. The resulting ontology covers symptoms and signs, all the types of pneumonia, antecedents, pathogens, and diagnostic testing. The first evaluation results show that most of the terms are covered by the ontology. This work is still in progress and represents a first and major step toward a development of a diagnosis decision support system for pneumonia. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Clinical%20decision%20support%20system" title="Clinical decision support system">Clinical decision support system</a>, <a href="https://publications.waset.org/abstracts/search?q=Diagnostic%20errors" title=" Diagnostic errors"> Diagnostic errors</a>, <a href="https://publications.waset.org/abstracts/search?q=Ontology" title=" Ontology"> Ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=Pneumonia" title=" Pneumonia"> Pneumonia</a> </p> <a href="https://publications.waset.org/abstracts/88337/design-of-a-pneumonia-ontology-for-diagnosis-decision-support-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/88337.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">189</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3450</span> User Guidance for Effective Query Interpretation in Natural Language Interfaces to Ontologies</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Aliyu%20Isah%20Agaie">Aliyu Isah Agaie</a>, <a href="https://publications.waset.org/abstracts/search?q=Masrah%20Azrifah%20Azmi%20Murad"> Masrah Azrifah Azmi Murad</a>, <a href="https://publications.waset.org/abstracts/search?q=Nurfadhlina%20Mohd%20Sharef"> Nurfadhlina Mohd Sharef</a>, <a href="https://publications.waset.org/abstracts/search?q=Aida%20Mustapha"> Aida Mustapha </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Natural Language Interfaces typically support a restricted language and also have scopes and limitations that naïve users are unaware of, resulting in errors when the users attempt to retrieve information from ontologies. To overcome this challenge, an auto-suggest feature is introduced into the querying process where users are guided through the querying process using interactive query construction system. Guiding users to formulate their queries, while providing them with an unconstrained (or almost unconstrained) way to query the ontology results in better interpretation of the query and ultimately lead to an effective search. The approach described in this paper is unobtrusive and subtly guides the users, so that they have a choice of either selecting from the suggestion list or typing in full. The user is not coerced into accepting system suggestions and can express himself using fragments or full sentences. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=auto-suggest" title="auto-suggest">auto-suggest</a>, <a href="https://publications.waset.org/abstracts/search?q=expressiveness" title=" expressiveness"> expressiveness</a>, <a href="https://publications.waset.org/abstracts/search?q=habitability" title=" habitability"> habitability</a>, <a href="https://publications.waset.org/abstracts/search?q=natural%20language%20interface" title=" natural language interface"> natural language interface</a>, <a href="https://publications.waset.org/abstracts/search?q=query%20interpretation" title=" query interpretation"> query interpretation</a>, <a href="https://publications.waset.org/abstracts/search?q=user%20guidance" title=" user guidance"> user guidance</a> </p> <a href="https://publications.waset.org/abstracts/42815/user-guidance-for-effective-query-interpretation-in-natural-language-interfaces-to-ontologies" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/42815.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">474</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3449</span> Linguistic Insights Improve Semantic Technology in Medical Research and Patient Self-Management Contexts</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=William%20Michael%20Short">William Michael Short</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Semantic Web’ technologies such as the Unified Medical Language System Metathesaurus, SNOMED-CT, and MeSH have been touted as transformational for the way users access online medical and health information, enabling both the automated analysis of natural-language data and the integration of heterogeneous healthrelated resources distributed across the Internet through the use of standardized terminologies that capture concepts and relationships between concepts that are expressed differently across datasets. However, the approaches that have so far characterized ‘semantic bioinformatics’ have not yet fulfilled the promise of the Semantic Web for medical and health information retrieval applications. This paper argues within the perspective of cognitive linguistics and cognitive anthropology that four features of human meaning-making must be taken into account before the potential of semantic technologies can be realized for this domain. First, many semantic technologies operate exclusively at the level of the word. However, texts convey meanings in ways beyond lexical semantics. For example, transitivity patterns (distributions of active or passive voice) and modality patterns (configurations of modal constituents like may, might, could, would, should) convey experiential and epistemic meanings that are not captured by single words. Language users also naturally associate stretches of text with discrete meanings, so that whole sentences can be ascribed senses similar to the senses of words (so-called ‘discourse topics’). Second, natural language processing systems tend to operate according to the principle of ‘one token, one tag’. For instance, occurrences of the word sound must be disambiguated for part of speech: in context, is sound a noun or a verb or an adjective? In syntactic analysis, deterministic annotation methods may be acceptable. But because natural language utterances are typically characterized by polyvalency and ambiguities of all kinds (including intentional ambiguities), such methods leave the meanings of texts highly impoverished. Third, ontologies tend to be disconnected from everyday language use and so struggle in cases where single concepts are captured through complex lexicalizations that involve profile shifts or other embodied representations. More problematically, concept graphs tend to capture ‘expert’ technical models rather than ‘folk’ models of knowledge and so may not match users’ common-sense intuitions about the organization of concepts in prototypical structures rather than Aristotelian categories. Fourth, and finally, most ontologies do not recognize the pervasively figurative character of human language. However, since the time of Galen the widespread use of metaphor in the linguistic usage of both medical professionals and lay persons has been recognized. In particular, metaphor is a well-documented linguistic tool for communicating experiences of pain. Because semantic medical knowledge-bases are designed to help capture variations within technical vocabularies – rather than the kinds of conventionalized figurative semantics that practitioners as well as patients actually utilize in clinical description and diagnosis – they fail to capture this dimension of linguistic usage. The failure of semantic technologies in these respects degrades the efficiency and efficacy not only of medical research, where information retrieval inefficiencies can lead to direct financial costs to organizations, but also of care provision, especially in contexts of patients’ self-management of complex medical conditions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ambiguity" title="ambiguity">ambiguity</a>, <a href="https://publications.waset.org/abstracts/search?q=bioinformatics" title=" bioinformatics"> bioinformatics</a>, <a href="https://publications.waset.org/abstracts/search?q=language" title=" language"> language</a>, <a href="https://publications.waset.org/abstracts/search?q=meaning" title=" meaning"> meaning</a>, <a href="https://publications.waset.org/abstracts/search?q=metaphor" title=" metaphor"> metaphor</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology" title=" ontology"> ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=semantic%20web" title=" semantic web"> semantic web</a>, <a href="https://publications.waset.org/abstracts/search?q=semantics" title=" semantics"> semantics</a> </p> <a href="https://publications.waset.org/abstracts/154574/linguistic-insights-improve-semantic-technology-in-medical-research-and-patient-self-management-contexts" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/154574.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">132</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3448</span> Obsession of Time and the New Musical Ontologies. The Concert for Saxophone, Daniel Kientzy and Orchestra by Myriam Marbe</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Dutica%20Luminita">Dutica Luminita</a> </p> <p class="card-text"><strong>Abstract:</strong></p> For the music composer Myriam Marbe the musical time and memory represent 2 (complementary) phenomena with conclusive impact on the settlement of new musical ontologies. Summarizing the most important achievements of the contemporary techniques of composition, her vision on the microform presented in The Concert for Daniel Kientzy, saxophone and orchestra transcends the linear and unidirectional time in favour of a flexible, multi-vectorial speech with spiral developments, where the sound substance is auto(re)generated by analogy with the fundamental processes of the memory. The conceptual model is of an archetypal essence, the music composer being concerned with identifying the mechanisms of the creation process, especially of those specific to the collective creation (of oral tradition). Hence the spontaneity of expression, improvisation tint, free rhythm, micro-interval intonation, coloristic-timbral universe dominated by multiphonics and unique sound effects. Hence the atmosphere of ritual, however purged by the primary connotations and reprojected into a wonderful spectacular space. The Concert is a work of artistic maturity and enforces respect, among others, by the timbral diversity of the three species of saxophone required by the music composer (baritone, sopranino and alt), in Part III Daniel Kientzy shows the performance of playing two saxophones concomitantly. The score of the music composer Myriam Marbe contains a deeply spiritualized music, full or archetypal symbols, a music whose drama suggests a real cinematographic movement. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=archetype" title="archetype">archetype</a>, <a href="https://publications.waset.org/abstracts/search?q=chronogenesis" title=" chronogenesis"> chronogenesis</a>, <a href="https://publications.waset.org/abstracts/search?q=concert" title=" concert"> concert</a>, <a href="https://publications.waset.org/abstracts/search?q=multiphonics" title=" multiphonics"> multiphonics</a> </p> <a href="https://publications.waset.org/abstracts/29047/obsession-of-time-and-the-new-musical-ontologies-the-concert-for-saxophone-daniel-kientzy-and-orchestra-by-myriam-marbe" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/29047.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">543</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3447</span> A Comparative Study of Approaches in User-Centred Health Information Retrieval</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Harsh%20Thakkar">Harsh Thakkar</a>, <a href="https://publications.waset.org/abstracts/search?q=Ganesh%20Iyer"> Ganesh Iyer</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we survey various user-centered or context-based biomedical health information retrieval systems. We present and discuss the performance of systems submitted in CLEF eHealth 2014 Task 3 for this purpose. We classify and focus on comparing the two most prevalent retrieval models in biomedical information retrieval namely: Language Model (LM) and Vector Space Model (VSM). We also report on the effectiveness of using external medical resources and ontologies like MeSH, Metamap, UMLS, etc. We observed that the LM based retrieval systems outperform VSM based systems on various fronts. From the results we conclude that the state-of-art system scores for MAP was 0.4146, P@10 was 0.7560 and NDCG@10 was 0.7445, respectively. All of these score were reported by systems built on language modeling approaches. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=clinical%20document%20retrieval" title="clinical document retrieval">clinical document retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=concept-based%20information%20retrieval" title=" concept-based information retrieval"> concept-based information retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=query%20expansion" title=" query expansion"> query expansion</a>, <a href="https://publications.waset.org/abstracts/search?q=language%20models" title=" language models"> language models</a>, <a href="https://publications.waset.org/abstracts/search?q=vector%20space%20models" title=" vector space models"> vector space models</a> </p> <a href="https://publications.waset.org/abstracts/57392/a-comparative-study-of-approaches-in-user-centred-health-information-retrieval" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/57392.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">320</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3446</span> A Lexicographic Approach to Obstacles Identified in the Ontological Representation of the Tree of Life</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sandra%20Young">Sandra Young</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The biodiversity literature is vast and heterogeneous. In today’s data age, numbers of data integration and standardisation initiatives aim to facilitate simultaneous access to all the literature across biodiversity domains for research and forecasting purposes. Ontologies are being used increasingly to organise this information, but the rationalisation intrinsic to ontologies can hit obstacles when faced with the intrinsic fluidity and inconsistency found in the domains comprising biodiversity. Essentially the problem is a conceptual one: biological taxonomies are formed on the basis of specific, physical specimens yet nomenclatural rules are used to provide labels to describe these physical objects. These labels are ambiguous representations of the physical specimen. An example of this is with the genus Melpomene, the scientific nomenclatural representation of a genus of ferns, but also for a genus of spiders. The physical specimens for each of these are vastly different, but they have been assigned the same nomenclatural reference. While there is much research into the conceptual stability of the taxonomic concept versus the nomenclature used, to the best of our knowledge as yet no research has looked empirically at the literature to see the conceptual plurality or singularity of the use of these species’ names, the linguistic representation of a physical entity. Language itself uses words as symbols to represent real world concepts, whether physical entities or otherwise, and as such lexicography has a well-founded history in the conceptual mapping of words in context for dictionary making. This makes it an ideal candidate to explore this problem. The lexicographic approach uses corpus-based analysis to look at word use in context, with a specific focus on collocated word frequencies (the frequencies of words used in specific grammatical and collocational contexts). It allows for inconsistencies and contradictions in the source data and in fact includes these in the word characterisation so that 100% of the available evidence is counted. Corpus analysis is indeed suggested as one of the ways to identify concepts for ontology building, because of its ability to look empirically at data and show patterns in language usage, which can indicate conceptual ideas which go beyond words themselves. In this sense it could potentially be used to identify if the hierarchical structures present within the empirical body of literature match those which have been identified in ontologies created to represent them. The first stages of this research have revealed a hierarchical structure that becomes apparent in the biodiversity literature when annotating scientific species’ names, common names and more general names as classes, which will be the focus of this paper. The next step in the research is focusing on a larger corpus in which specific words can be analysed and then compared with existing ontological structures looking at the same material, to evaluate the methods by means of an alternative perspective. This research aims to provide evidence as to the validity of the current methods in knowledge representation for biological entities, and also shed light on the way that scientific nomenclature is used within the literature. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ontology" title="ontology">ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=biodiversity" title=" biodiversity"> biodiversity</a>, <a href="https://publications.waset.org/abstracts/search?q=lexicography" title=" lexicography"> lexicography</a>, <a href="https://publications.waset.org/abstracts/search?q=knowledge%20representation" title=" knowledge representation"> knowledge representation</a>, <a href="https://publications.waset.org/abstracts/search?q=corpus%20linguistics" title=" corpus linguistics"> corpus linguistics</a> </p> <a href="https://publications.waset.org/abstracts/102884/a-lexicographic-approach-to-obstacles-identified-in-the-ontological-representation-of-the-tree-of-life" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/102884.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">137</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3445</span> Ontology-Based Approach for Temporal Semantic Modeling of Social Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sou%C3%A2ad%20Boudebza">Souâad Boudebza</a>, <a href="https://publications.waset.org/abstracts/search?q=Omar%20Nouali"> Omar Nouali</a>, <a href="https://publications.waset.org/abstracts/search?q=Fai%C3%A7al%20Azouaou"> Faiçal Azouaou</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Social networks have recently gained a growing interest on the web. Traditional formalisms for representing social networks are static and suffer from the lack of semantics. In this paper, we will show how semantic web technologies can be used to model social data. The SemTemp ontology aligns and extends existing ontologies such as FOAF, SIOC, SKOS and OWL-Time to provide a temporal and semantically rich description of social data. We also present a modeling scenario to illustrate how our ontology can be used to model social networks. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ontology" title="ontology">ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=semantic%20web" title=" semantic web"> semantic web</a>, <a href="https://publications.waset.org/abstracts/search?q=social%20network" title=" social network"> social network</a>, <a href="https://publications.waset.org/abstracts/search?q=temporal%20modeling" title=" temporal modeling"> temporal modeling</a> </p> <a href="https://publications.waset.org/abstracts/42125/ontology-based-approach-for-temporal-semantic-modeling-of-social-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/42125.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">386</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3444</span> Fuzzy Semantic Annotation of Web Resources </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sahar%20Ma%C3%A2lej%20Dammak">Sahar Maâlej Dammak</a>, <a href="https://publications.waset.org/abstracts/search?q=Anis%20Jedidi"> Anis Jedidi</a>, <a href="https://publications.waset.org/abstracts/search?q=Rafik%20Bouaziz"> Rafik Bouaziz</a> </p> <p class="card-text"><strong>Abstract:</strong></p> With the great mass of pages managed through the world, and especially with the advent of the Web, their manual annotation is impossible. We focus, in this paper, on the semiautomatic annotation of the web pages. We propose an approach and a framework for semantic annotation of web pages entitled “Querying Web”. Our solution is an enhancement of the first result of annotation done by the “Semantic Radar” Plug-in on the web resources, by annotations using an enriched domain ontology. The concepts of the result of Semantic Radar may be connected to several terms of the ontology, but connections may be uncertain. We represent annotations as possibility distributions. We use the hierarchy defined in the ontology to compute degrees of possibilities. We want to achieve an automation of the fuzzy semantic annotation of web resources. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20semantic%20annotation" title="fuzzy semantic annotation">fuzzy semantic annotation</a>, <a href="https://publications.waset.org/abstracts/search?q=semantic%20web" title=" semantic web"> semantic web</a>, <a href="https://publications.waset.org/abstracts/search?q=domain%20ontologies" title=" domain ontologies"> domain ontologies</a>, <a href="https://publications.waset.org/abstracts/search?q=querying%20web" title=" querying web"> querying web</a> </p> <a href="https://publications.waset.org/abstracts/1854/fuzzy-semantic-annotation-of-web-resources" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/1854.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">374</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3443</span> Clustering-Based Computational Workload Minimization in Ontology Matching</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mansir%20Abubakar">Mansir Abubakar</a>, <a href="https://publications.waset.org/abstracts/search?q=Hazlina%20Hamdan"> Hazlina Hamdan</a>, <a href="https://publications.waset.org/abstracts/search?q=Norwati%20Mustapha"> Norwati Mustapha</a>, <a href="https://publications.waset.org/abstracts/search?q=Teh%20Noranis%20Mohd%20Aris"> Teh Noranis Mohd Aris</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In order to build a matching pattern for each class correspondences of ontology, it is required to specify a set of attribute correspondences across two corresponding classes by clustering. Clustering reduces the size of potential attribute correspondences considered in the matching activity, which will significantly reduce the computation workload; otherwise, all attributes of a class should be compared with all attributes of the corresponding class. Most existing ontology matching approaches lack scalable attributes discovery methods, such as cluster-based attribute searching. This problem makes ontology matching activity computationally expensive. It is therefore vital in ontology matching to design a scalable element or attribute correspondence discovery method that would reduce the size of potential elements correspondences during mapping thereby reduce the computational workload in a matching process as a whole. The objective of this work is 1) to design a clustering method for discovering similar attributes correspondences and relationships between ontologies, 2) to discover element correspondences by classifying elements of each class based on element’s value features using K-medoids clustering technique. Discovering attribute correspondence is highly required for comparing instances when matching two ontologies. During the matching process, any two instances across two different data sets should be compared to their attribute values, so that they can be regarded to be the same or not. Intuitively, any two instances that come from classes across which there is a class correspondence are likely to be identical to each other. Besides, any two instances that hold more similar attribute values are more likely to be matched than the ones with less similar attribute values. Most of the time, similar attribute values exist in the two instances across which there is an attribute correspondence. This work will present how to classify attributes of each class with K-medoids clustering, then, clustered groups to be mapped by their statistical value features. We will also show how to map attributes of a clustered group to attributes of the mapped clustered group, generating a set of potential attribute correspondences that would be applied to generate a matching pattern. The K-medoids clustering phase would largely reduce the number of attribute pairs that are not corresponding for comparing instances as only the coverage probability of attributes pairs that reaches 100% and attributes above the specified threshold can be considered as potential attributes for a matching. Using clustering will reduce the size of potential elements correspondences to be considered during mapping activity, which will in turn reduce the computational workload significantly. Otherwise, all element of the class in source ontology have to be compared with all elements of the corresponding classes in target ontology. K-medoids can ably cluster attributes of each class, so that a proportion of attribute pairs that are not corresponding would not be considered when constructing the matching pattern. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=attribute%20correspondence" title="attribute correspondence">attribute correspondence</a>, <a href="https://publications.waset.org/abstracts/search?q=clustering" title=" clustering"> clustering</a>, <a href="https://publications.waset.org/abstracts/search?q=computational%20workload" title=" computational workload"> computational workload</a>, <a href="https://publications.waset.org/abstracts/search?q=k-medoids%20clustering" title=" k-medoids clustering"> k-medoids clustering</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology%20matching" title=" ontology matching"> ontology matching</a> </p> <a href="https://publications.waset.org/abstracts/78369/clustering-based-computational-workload-minimization-in-ontology-matching" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/78369.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">248</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3442</span> Medical Images Enhancement Using New Dynamic Band Pass Filter</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdellatif%20Baba">Abdellatif Baba</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In order to facilitate medical images analysis by improving their quality and readability, we present in this paper a new dynamic band pass filter as a general and suitable operator for different types of medical images. Our objective is to enrich the details of any treated medical image to make it sufficiently clear enough to give an understood and simplified meaning even for unspecialized people in the medical domain. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=medical%20image%20enhancement" title="medical image enhancement">medical image enhancement</a>, <a href="https://publications.waset.org/abstracts/search?q=dynamic%20band%20pass%20filter" title=" dynamic band pass filter"> dynamic band pass filter</a>, <a href="https://publications.waset.org/abstracts/search?q=analysis%20improvement" title=" analysis improvement"> analysis improvement</a> </p> <a href="https://publications.waset.org/abstracts/14660/medical-images-enhancement-using-new-dynamic-band-pass-filter" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14660.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">289</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=medical%20ontologies&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=medical%20ontologies&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=medical%20ontologies&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=medical%20ontologies&page=5">5</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=medical%20ontologies&page=6">6</a></li> <li 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