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learning</title> <meta name="description" content="Search results for: ontology learning"> <meta name="keywords" content="ontology learning"> <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="ontology learning"> <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> 7342</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: ontology learning</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7342</span> A Study of Various Ontology Learning Systems from Text and a Look into Future</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fatima%20Al-Aswadi">Fatima Al-Aswadi</a>, <a href="https://publications.waset.org/abstracts/search?q=Chan%20Yong"> Chan Yong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> With the large volume of unstructured data that increases day by day on the web, the motivation of representing the knowledge in this data in the machine processable form is increased. Ontology is one of the major cornerstones of representing the information in a more meaningful way on the semantic Web. The goal of Ontology learning from text is to elicit and represent domain knowledge in the machine readable form. This paper aims to give a follow-up review on the ontology learning systems from text and some of their defects. Furthermore, it discusses how far the ontology learning process will enhance in the future. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=concept%20discovery" title="concept discovery">concept discovery</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title=" deep learning"> deep learning</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology%20learning" title=" ontology learning"> ontology learning</a>, <a href="https://publications.waset.org/abstracts/search?q=semantic%20relation" title=" semantic relation"> semantic relation</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/63156/a-study-of-various-ontology-learning-systems-from-text-and-a-look-into-future" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/63156.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">521</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">7341</span> An Ontology for Smart Learning Environments in Music Education</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Konstantinos%20Sofianos">Konstantinos Sofianos</a>, <a href="https://publications.waset.org/abstracts/search?q=Michail%20Stefanidakis"> Michail Stefanidakis</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Nowadays, despite the great advances in technology, most educational frameworks lack a strong educational design basis. E-learning has become prevalent, but it faces various challenges such as student isolation and lack of quality in the learning process. An intelligent learning system provides a student with educational material according to their learning background and learning preferences. It records full information about the student, such as demographic information, learning styles, and academic performance. This information allows the system to be fully adapted to the student’s needs. In this paper, we propose a framework and an ontology for music education, consisting of the learner model and all elements of the learning process (learning objects, teaching methods, learning activities, assessment). This framework can be integrated into an intelligent learning system and used for music education in schools for the development of professional skills and beyond. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=intelligent%20learning%20systems" title="intelligent learning systems">intelligent learning systems</a>, <a href="https://publications.waset.org/abstracts/search?q=e-learning" title=" e-learning"> e-learning</a>, <a href="https://publications.waset.org/abstracts/search?q=music%20education" title=" music education"> music education</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> </p> <a href="https://publications.waset.org/abstracts/153256/an-ontology-for-smart-learning-environments-in-music-education" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/153256.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">7340</span> Development of Fuzzy Logic Control Ontology for E-Learning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Sollehhuddin%20A.%20Jalil">Muhammad Sollehhuddin A. Jalil</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohd%20Ibrahim%20Shapiai"> Mohd Ibrahim Shapiai</a>, <a href="https://publications.waset.org/abstracts/search?q=Rubiyah%20Yusof"> Rubiyah Yusof</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Nowadays, ontology is common in many areas like artificial intelligence, bioinformatics, e-commerce, education and many more. Ontology is one of the focus areas in the field of Information Retrieval. The purpose of an ontology is to describe a conceptual representation of concepts and their relationships within a particular domain. In other words, ontology provides a common vocabulary for anyone who needs to share information in the domain. There are several ontology domains in various fields including engineering and non-engineering knowledge. However, there are only a few available ontology for engineering knowledge. Fuzzy logic as engineering knowledge is still not available as ontology domain. In general, fuzzy logic requires step-by-step guidelines and instructions of lab experiments. In this study, we presented domain ontology for Fuzzy Logic Control (FLC) knowledge. We give Table of Content (ToC) with middle strategy based on the Uschold and King method to develop FLC ontology. The proposed framework is developed using Protégé as the ontology tool. The Protégé’s ontology reasoner, known as the Pellet reasoner is then used to validate the presented framework. The presented framework offers better performance based on consistency and classification parameter index. In general, this ontology can provide a platform to anyone who needs to understand FLC knowledge. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=engineering%20knowledge" title="engineering knowledge">engineering knowledge</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20logic%20control%20ontology" title=" fuzzy logic control ontology"> fuzzy logic control ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology%20development" title=" ontology development"> ontology development</a>, <a href="https://publications.waset.org/abstracts/search?q=table%20of%20content" title=" table of content"> table of content</a> </p> <a href="https://publications.waset.org/abstracts/54717/development-of-fuzzy-logic-control-ontology-for-e-learning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/54717.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">299</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">7339</span> OSEME: A Smart Learning Environment for Music Education</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Konstantinos%20Sofianos">Konstantinos Sofianos</a>, <a href="https://publications.waset.org/abstracts/search?q=Michael%20Stefanidakis"> Michael Stefanidakis</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Nowadays, advances in information and communication technologies offer a range of opportunities for new approaches, methods, and tools in the field of education and training. Teacher-centered learning has changed to student-centered learning. E-learning has now matured and enables the design and construction of intelligent learning systems. A smart learning system fully adapts to a student's needs and provides them with an education based on their preferences, learning styles, and learning backgrounds. It is a wise friend and available at any time, in any place, and with any digital device. In this paper, we propose an intelligent learning system, which includes an ontology with all elements of the learning process (learning objects, learning activities) and a massive open online course (MOOC) system. This intelligent learning system can be used in music education. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=intelligent%20learning%20systems" title="intelligent learning systems">intelligent learning systems</a>, <a href="https://publications.waset.org/abstracts/search?q=e-learning" title=" e-learning"> e-learning</a>, <a href="https://publications.waset.org/abstracts/search?q=music%20education" title=" music education"> music education</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> </p> <a href="https://publications.waset.org/abstracts/168933/oseme-a-smart-learning-environment-for-music-education" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/168933.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">311</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">7338</span> Ontology-Navigated Tutoring System for Flipped-Mastery Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Masao%20Okabe">Masao Okabe</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Nowadays, in Japan, variety of students get into a university and one of the main roles of introductory courses for freshmen is to make such students well prepared for subsequent intermediate courses. For that purpose, the flipped-mastery model is not enough because videos usually used in a flipped classroom is not adaptive and does not fit all freshmen with different academic performances. This paper proposes an ontology-navigated tutoring system called EduGraph. Using EduGraph, students can prepare for and review a class, in a more flexibly personalizable way than by videos. Structuralizing learning materials by its ontology, EduGraph also helps students integrate what they learn as knowledge, and makes learning materials sharable. EduGraph was used for an introductory course for freshmen. This application suggests that EduGraph is effective. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20e-learning" title="adaptive e-learning">adaptive e-learning</a>, <a href="https://publications.waset.org/abstracts/search?q=flipped%20classroom" title=" flipped classroom"> flipped classroom</a>, <a href="https://publications.waset.org/abstracts/search?q=mastery%20learning" title=" mastery learning"> mastery learning</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology" title=" ontology"> ontology</a> </p> <a href="https://publications.waset.org/abstracts/51709/ontology-navigated-tutoring-system-for-flipped-mastery-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/51709.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">280</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">7337</span> Constructing a Probabilistic Ontology from a DBLP Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Emna%20Hlel">Emna Hlel</a>, <a href="https://publications.waset.org/abstracts/search?q=Salma%20Jamousi"> Salma Jamousi</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdelmajid%20Ben%20Hamadou"> Abdelmajid Ben Hamadou</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Every model for knowledge representation to model real-world applications must be able to cope with the effects of uncertain phenomena. One of main defects of classical ontology is its inability to represent and reason with uncertainty. To remedy this defect, we try to propose a method to construct probabilistic ontology for integrating uncertain information in an ontology modeling a set of basic publications DBLP (Digital Bibliography & Library Project) using a probabilistic model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=classical%20ontology" title="classical ontology">classical ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=probabilistic%20ontology" title=" probabilistic ontology"> probabilistic ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=uncertainty" title=" uncertainty"> uncertainty</a>, <a href="https://publications.waset.org/abstracts/search?q=Bayesian%20network" title=" Bayesian network"> Bayesian network</a> </p> <a href="https://publications.waset.org/abstracts/24225/constructing-a-probabilistic-ontology-from-a-dblp-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/24225.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">347</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">7336</span> Building Semantic-Relatedness Thai Word Ontology for Semantic Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gridaphat%20Sriharee">Gridaphat Sriharee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Building semantic-relatedness Thai word ontology can be implemented by considering word forms and word meaning. This research proposed the methodology for building the ontology, which can be used for semantic analysis. There are four categories of words: similar form and the same meaning, similar form and similar meaning, different form and opposite/same meaning, and different form and similar meaning, which will be used as initial words for building the proposed ontology. Extension of the ontology can be augmented by considering the messages that give the meaning of the word from the dictionaries. Exploiting WordNet to construct the proposed ontology was investigated and discussed. The proposed ontology was evaluated for its quality. With the proposed methodology, it is promising that the constructed ontology is a well-defined ontology. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Thai" title="Thai">Thai</a>, <a href="https://publications.waset.org/abstracts/search?q=NLP" title=" NLP"> NLP</a>, <a href="https://publications.waset.org/abstracts/search?q=semantics" title=" semantics"> semantics</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology" title=" ontology"> ontology</a> </p> <a href="https://publications.waset.org/abstracts/157354/building-semantic-relatedness-thai-word-ontology-for-semantic-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/157354.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">93</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">7335</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">7334</span> Software Architectural Design Ontology</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Irfan%20Marwat">Muhammad Irfan Marwat</a>, <a href="https://publications.waset.org/abstracts/search?q=Sadaqat%20Jan"> Sadaqat Jan</a>, <a href="https://publications.waset.org/abstracts/search?q=Syed%20Zafar%20Ali%20Shah"> Syed Zafar Ali Shah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Software architecture plays a key role in software development but absence of formal description of software architecture causes different impede in software development. To cope with these difficulties, ontology has been used as artifact. This paper proposes ontology for software architectural design based on IEEE model for architecture description and Kruchten 4+1 model for viewpoints classification. For categorization of style and views, ISO/IEC 42010 has been used. Corpus method has been used to evaluate ontology. The main aim of the proposed ontology is to classify and locate software architectural design information. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=semantic-based%20software%20architecture" title="semantic-based software architecture">semantic-based software architecture</a>, <a href="https://publications.waset.org/abstracts/search?q=software%20architecture" title=" software architecture"> software architecture</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology" title=" ontology"> ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=software%20engineering" title=" software engineering"> software engineering</a> </p> <a href="https://publications.waset.org/abstracts/2056/software-architectural-design-ontology" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2056.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">548</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">7333</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">7332</span> Semantic Platform for Adaptive and Collaborative e-Learning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Massra%20M.%20Sabeima">Massra M. Sabeima</a>, <a href="https://publications.waset.org/abstracts/search?q=Myriam%20lamolle"> Myriam lamolle</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamedade%20Farouk%20Nanne"> Mohamedade Farouk Nanne</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Adapting the learning resources of an e-learning system to the characteristics of the learners is an important aspect to consider when designing an adaptive e-learning system. However, this adaptation is not a simple process; it requires the extraction, analysis, and modeling of user information. This implies a good representation of the user's profile, which is the backbone of the adaptation process. Moreover, during the e-learning process, collaboration with similar users (same geographic province or knowledge context) is important. Productive collaboration motivates users to continue or not abandon the course and increases the assimilation of learning objects. The contribution of this work is the following: we propose an adaptive e-learning semantic platform to recommend learning resources to learners, using ontology to model the user profile and the course content, furthermore an implementation of a multi-agent system able to progressively generate the learning graph (taking into account the user's progress, and the changes that occur) for each user during the learning process, and to synchronize the users who collaborate on a learning object. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptative%20learning" title="adaptative learning">adaptative learning</a>, <a href="https://publications.waset.org/abstracts/search?q=collaboration" title=" collaboration"> collaboration</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-agent" title=" multi-agent"> multi-agent</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology" title=" ontology"> ontology</a> </p> <a href="https://publications.waset.org/abstracts/144619/semantic-platform-for-adaptive-and-collaborative-e-learning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/144619.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">175</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">7331</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">7330</span> Annotation Ontology for Semantic Web Development</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hadeel%20Al%20Obaidy">Hadeel Al Obaidy</a>, <a href="https://publications.waset.org/abstracts/search?q=Amani%20Al%20Heela"> Amani Al Heela</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The main purpose of this paper is to examine the concept of semantic web and the role that ontology and semantic annotation plays in the development of semantic web services. The paper focuses on semantic web infrastructure illustrating how ontology and annotation work to provide the learning capabilities for building content semantically. To improve productivity and quality of software, the paper applies approaches, notations and techniques offered by software engineering. It proposes a conceptual model to develop semantic web services for the infrastructure of web information retrieval system of digital libraries. The developed system uses ontology and annotation to build a knowledge based system to define and link the meaning of a web content to retrieve information for users’ queries. The results are more relevant through keywords and ontology rule expansion that will be more accurate to satisfy the requested information. The level of results accuracy would be enhanced since the query semantically analyzed work with the conceptual architecture of the proposed system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=semantic%20web%20services" title="semantic web services">semantic web services</a>, <a href="https://publications.waset.org/abstracts/search?q=software%20engineering" title=" software engineering"> software engineering</a>, <a href="https://publications.waset.org/abstracts/search?q=semantic%20library" title=" semantic library"> semantic library</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> </p> <a href="https://publications.waset.org/abstracts/103442/annotation-ontology-for-semantic-web-development" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/103442.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">173</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">7329</span> Development of the Ontology of Engineering Design Complexity</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Victor%20E.%20%20Lopez">Victor E. Lopez</a>, <a href="https://publications.waset.org/abstracts/search?q=L.%20Dale%20Thomas"> L. Dale Thomas</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As engineered systems become more complex, the difficulty associated with predicting, developing, and operating engineered systems also increases, resulting in increased costs, failure rates, and unexpected consequences. Successfully managing the complexity of the system should reduce these negative consequences. The study of complexity in the context of engineering development has suffered due to the ambiguity of the nature of complexity, what makes a system complex and how complexity translates to real world engineering attributes and consequences. This paper argues that the use of an ontology of engineering design complexity would i) improve the clarity of the research being performed by allowing researchers to use a common conceptualization of complexity, with more precise terminology, and ii) elucidate the connections between certain types of complexity and their consequences for system development. The ontology comprises concepts of complexity found in the literature and the different relations that exists between them. The ontology maps different complexity concepts such as structural complexity, creation complexity, and information entropy, and then relates the to system aspects such as interfaces, development effort, and modularity. The ontology is represented using the Web Ontology Language (OWL). This paper presents the current status of the ontology of engineering design complexity, the main challenges encountered, and the future plans for the ontology. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=design%20complexity" title="design complexity">design complexity</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology" title=" ontology"> ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=design%20effort" title=" design effort"> design effort</a>, <a href="https://publications.waset.org/abstracts/search?q=complexity%20ontology" title=" complexity ontology"> complexity ontology</a> </p> <a href="https://publications.waset.org/abstracts/138740/development-of-the-ontology-of-engineering-design-complexity" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/138740.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">187</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">7328</span> E-Learning Recommender System Based on Collaborative Filtering and Ontology</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=John%20Tarus">John Tarus</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhendong%20Niu"> Zhendong Niu</a>, <a href="https://publications.waset.org/abstracts/search?q=Bakhti%20Khadidja"> Bakhti Khadidja</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In recent years, e-learning recommender systems has attracted great attention as a solution towards addressing the problem of information overload in e-learning environments and providing relevant recommendations to online learners. E-learning recommenders continue to play an increasing educational role in aiding learners to find appropriate learning materials to support the achievement of their learning goals. Although general recommender systems have recorded significant success in solving the problem of information overload in e-commerce domains and providing accurate recommendations, e-learning recommender systems on the other hand still face some issues arising from differences in learner characteristics such as learning style, skill level and study level. Conventional recommendation techniques such as collaborative filtering and content-based deal with only two types of entities namely users and items with their ratings. These conventional recommender systems do not take into account the learner characteristics in their recommendation process. Therefore, conventional recommendation techniques cannot make accurate and personalized recommendations in e-learning environment. In this paper, we propose a recommendation technique combining collaborative filtering and ontology to recommend personalized learning materials to online learners. Ontology is used to incorporate the learner characteristics into the recommendation process alongside the ratings while collaborate filtering predicts ratings and generate recommendations. Furthermore, ontological knowledge is used by the recommender system at the initial stages in the absence of ratings to alleviate the cold-start problem. Evaluation results show that our proposed recommendation technique outperforms collaborative filtering on its own in terms of personalization and recommendation accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=collaborative%20filtering" title="collaborative filtering">collaborative filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=e-learning" title=" e-learning"> e-learning</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology" title=" ontology"> ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=recommender%20system" title=" recommender system"> recommender system</a> </p> <a href="https://publications.waset.org/abstracts/64364/e-learning-recommender-system-based-on-collaborative-filtering-and-ontology" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/64364.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">379</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">7327</span> Knowledge and Ontology Engineering in Continuous Monitoring of Production Systems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Maciej%20Zar%C4%99ba">Maciej Zaręba</a>, <a href="https://publications.waset.org/abstracts/search?q=S%C5%82awomir%20Lasota"> Sławomir Lasota</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The monitoring of manufacturing processes is an important issue in nowadays ERP systems. The identification and analysis of appropriate data for the units that take part in the production process are ones of the most crucial problems. In this paper, the authors introduce a new approach towards modelling the relation between production units, signals, and factors possible to obtain from the production system. The main idea for the system is based on the ontology of production units. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=manufacturing%20operation%20management" title="manufacturing operation management">manufacturing operation management</a>, <a href="https://publications.waset.org/abstracts/search?q=OWL" title=" OWL"> OWL</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology%20implementation" title=" ontology implementation"> ontology implementation</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology%20modeling" title=" ontology modeling"> ontology modeling</a> </p> <a href="https://publications.waset.org/abstracts/155251/knowledge-and-ontology-engineering-in-continuous-monitoring-of-production-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/155251.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">120</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">7326</span> A Description Logics Based Approach for Building Multi-Viewpoints Ontologies</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Hemam">M. Hemam</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Djezzar"> M. Djezzar</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20Djouad"> T. Djouad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We are interested in the problem of building an ontology in a heterogeneous organization, by taking into account different viewpoints and different terminologies of communities in the organization. Such ontology, that we call multi-viewpoint ontology, confers to the same universe of discourse, several partial descriptions, where each one is relative to a particular viewpoint. In addition, these partial descriptions share at global level, ontological elements constituent a consensus between the various viewpoints. In order to provide response elements to this problem we define a multi-viewpoints knowledge model based on viewpoint and ontology notions. The multi-viewpoints knowledge model is used to formalize the multi-viewpoints ontology in description logics language. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=description%20logic" title="description logic">description logic</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=ontology" title=" ontology"> ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=viewpoint" title=" viewpoint"> viewpoint</a> </p> <a href="https://publications.waset.org/abstracts/47476/a-description-logics-based-approach-for-building-multi-viewpoints-ontologies" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/47476.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">313</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">7325</span> Ontology-Based Representation of Islamic Rules to Perform Salah</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hamza%20Zafar">Hamza Zafar</a>, <a href="https://publications.waset.org/abstracts/search?q=Quratulain%20Rajput"> Quratulain Rajput</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Salah (نماز ) is one of five pillars of Islam and obligatory for every Muslims. However, due to the lack of Islamic knowledge it might be very difficult for a layperson to perform it correctly. This paper presents an ontology based representation of Islamic rules to perform Salah. The Salah ontology has been built under the guidance of domain expert in light of Quran and Hadith. The ontology consists of basic concepts as well as relationship among concepts and constraints on them. The basic concepts include cleanness, body cover, Salah timing and steps to perform Salah. The SWRL rule language has been used to represent rule to determine whether the Salah performed correctly or it should be repeated. Finally, we evaluate the use of the Salat ontology through user’s example queries using SPARQL queries. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=prayer" title="prayer">prayer</a>, <a href="https://publications.waset.org/abstracts/search?q=salah" title=" salah"> salah</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology" title=" ontology"> ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=SPARQL%20queries" title=" SPARQL queries"> SPARQL queries</a>, <a href="https://publications.waset.org/abstracts/search?q=reasoning" title=" reasoning"> reasoning</a> </p> <a href="https://publications.waset.org/abstracts/49552/ontology-based-representation-of-islamic-rules-to-perform-salah" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/49552.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">417</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">7324</span> Deep Learning Based-Object-classes Semantic Classification of Arabic Texts</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Imen%20Elleuch">Imen Elleuch</a>, <a href="https://publications.waset.org/abstracts/search?q=Wael%20Ouarda"> Wael Ouarda</a>, <a href="https://publications.waset.org/abstracts/search?q=Gargouri%20Bilel"> Gargouri Bilel</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We proposes in this paper a Deep Learning based approach to classify text in order to enrich an Arabic ontology based on the objects classes of Gaston Gross. Those object classes are defined by taking into account the syntactic and semantic features of the treated language. Thus, our proposed approach is a hybrid one. In fact, it is based on the one hand on the object classes that represents a knowledge based-approach on classification of text and in the other hand it uses the deep learning approach that use the word embedding-based-approach to classify text. We have applied our proposed approach on a corpus constructed from an Arabic dictionary. The obtained semantic classification of text will enrich the Arabic objects classes ontology. In fact, new classes can be added to the ontology or an expansion of the features that characterizes each object class can be updated. The obtained results are compared to a similar work that treats the same object with a classical linguistic approach for the semantic classification of text. This comparison highlight our hybrid proposed approach that can be ameliorated by broaden the dataset used in the deep learning process. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=deep-learning%20approach" title="deep-learning approach">deep-learning approach</a>, <a href="https://publications.waset.org/abstracts/search?q=object-classes" title=" object-classes"> object-classes</a>, <a href="https://publications.waset.org/abstracts/search?q=semantic%20classification" title=" semantic classification"> semantic classification</a>, <a href="https://publications.waset.org/abstracts/search?q=Arabic" title=" Arabic"> Arabic</a> </p> <a href="https://publications.waset.org/abstracts/176532/deep-learning-based-object-classes-semantic-classification-of-arabic-texts" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/176532.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">87</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">7323</span> A Virtual Reality Cybersecurity Training Knowledge-Based Ontology</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shaila%20Rana">Shaila Rana</a>, <a href="https://publications.waset.org/abstracts/search?q=Wasim%20Alhamdani"> Wasim Alhamdani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Effective cybersecurity learning relies on an engaging, interactive, and entertaining activity that fosters positive learning outcomes. VR cybersecurity training may promote these aforementioned variables. However, a methodological approach and framework have not yet been created to allow trainers and educators to employ VR cybersecurity training methods to promote positive learning outcomes to the author’s best knowledge. Thus, this paper aims to create an approach that cybersecurity trainers can follow to create a VR cybersecurity training module. This methodology utilizes concepts from other cybersecurity training frameworks, such as NICE and CyTrONE. Other cybersecurity training frameworks do not incorporate the use of VR. VR training proposes unique challenges that cannot be addressed in current cybersecurity training frameworks. Subsequently, this ontology utilizes concepts unique to developing VR training to create a relevant methodology for creating VR cybersecurity training modules. The outcome of this research is to create a methodology that is relevant and useful for designing VR cybersecurity training modules. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=virtual%20reality%20cybersecurity%20training" title="virtual reality cybersecurity training">virtual reality cybersecurity training</a>, <a href="https://publications.waset.org/abstracts/search?q=VR%20cybersecurity%20training" title=" VR cybersecurity training"> VR cybersecurity training</a>, <a href="https://publications.waset.org/abstracts/search?q=traditional%20cybersecurity%20training" title=" traditional cybersecurity training"> traditional cybersecurity training</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology" title=" ontology"> ontology</a> </p> <a href="https://publications.waset.org/abstracts/138790/a-virtual-reality-cybersecurity-training-knowledge-based-ontology" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/138790.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> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7322</span> An Ontology for Semantic Enrichment of RFID Systems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Haitham%20S.%20Hamza">Haitham S. Hamza</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Maher"> Mohamed Maher</a>, <a href="https://publications.waset.org/abstracts/search?q=Shourok%20Alaa"> Shourok Alaa</a>, <a href="https://publications.waset.org/abstracts/search?q=Aya%20Khattab"> Aya Khattab</a>, <a href="https://publications.waset.org/abstracts/search?q=Hadeal%20Ismail"> Hadeal Ismail</a>, <a href="https://publications.waset.org/abstracts/search?q=Kamilia%20Hosny"> Kamilia Hosny</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Radio Frequency Identification (RFID) has become a key technology in the margining concept of Internet of Things (IoT). Naturally, business applications would require the deployment of various RFID systems that are developed by different vendors and use various data formats. This heterogeneity poses a real challenge in developing large-scale IoT systems with RFID as integration is becoming very complex and challenging. Semantic integration is a key approach to deal with this challenge. To do so, ontology for RFID systems need to be developed in order to annotated semantically RFID systems, and hence, facilitate their integration. Accordingly, in this paper, we propose ontology for RFID systems. The proposed ontology can be used to semantically enrich RFID systems, and hence, improve their usage and reasoning. The usage of the proposed ontology is explained through a simple scenario in the health care domain. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=RFID" title="RFID">RFID</a>, <a href="https://publications.waset.org/abstracts/search?q=semantic%20technology" title=" semantic technology"> semantic technology</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology" title=" ontology"> ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=sparql%20query%20language" title=" sparql query language"> sparql query language</a>, <a href="https://publications.waset.org/abstracts/search?q=heterogeneity" title=" heterogeneity"> heterogeneity</a> </p> <a href="https://publications.waset.org/abstracts/39376/an-ontology-for-semantic-enrichment-of-rfid-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/39376.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">471</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">7321</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">7320</span> Ontology-Driven Generation of Radiation Protection Procedures</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chamseddine%20Barki">Chamseddine Barki</a>, <a href="https://publications.waset.org/abstracts/search?q=Salam%20Labidi"> Salam Labidi</a>, <a href="https://publications.waset.org/abstracts/search?q=Hanen%20Boussi%20Rahmouni"> Hanen Boussi Rahmouni</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this article, we present the principle and suitable methodology for the design of a medical ontology that highlights the radiological and dosimetric knowledge, applied in diagnostic radiology and radiation-therapy. Our ontology, which we named «Onto.Rap», is the subject of radiation protection in medical and radiology centers by providing a standardized regulatory oversight. Thanks to its added values of knowledge-sharing, reuse and the ease of maintenance, this ontology tends to solve many problems. Of which we name the confusion between radiological procedures a practitioner might face while performing a patient radiological exam. Adding to it, the difficulties they might have in interpreting applicable patient radioprotection standards. Here, the ontology, thanks to its concepts simplification and expressiveness capabilities, can ensure an efficient classification of radiological procedures. It also provides an explicit representation of the relations between the different components of the studied concept. In fact, an ontology based-radioprotection expert system, when used in radiological center, could implement systematic radioprotection best practices during patient exam and a regulatory compliance service auditing afterwards. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=knowledge" title="knowledge">knowledge</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology" title=" ontology"> ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=radiation%20protection" title=" radiation protection"> radiation protection</a>, <a href="https://publications.waset.org/abstracts/search?q=radiology" title=" radiology"> radiology</a> </p> <a href="https://publications.waset.org/abstracts/60395/ontology-driven-generation-of-radiation-protection-procedures" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/60395.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">7319</span> On Supporting a Meta-Design Approach in Socio-Technical Ontology Engineering</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mesnan%20Silalahi">Mesnan Silalahi</a>, <a href="https://publications.waset.org/abstracts/search?q=Dana%20Indra%20Sensuse"> Dana Indra Sensuse</a>, <a href="https://publications.waset.org/abstracts/search?q=Indra%20Budi"> Indra Budi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Many research have revealed the fact of the complexity of ontology building process that there is a need to have a new approach which addresses the socio-technical aspects in the collaboration to reach a consensus. Meta-design approach is considered applicable as a method in the methodological model in a socio-technical ontology engineering. Principles in the meta-design framework is applied in the construction phases on the ontology. A portal is developed to support the meta-design principles requirements. To validate the methodological model semantic web applications were developed and integrated in the portal and also used as a way to show the usefulness of the ontology. The knowledge based system will be filled with data of Indonesian medicinal plants. By showing the usefulness of the developed ontology in a web semantic application, we motivate all stakeholders to participate in the development of knowledge based system of medicinal plants in Indonesia. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=socio-technical" title="socio-technical">socio-technical</a>, <a href="https://publications.waset.org/abstracts/search?q=metadesign" title=" metadesign"> metadesign</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology%20engineering%20methodology" title=" ontology engineering methodology"> ontology engineering methodology</a>, <a href="https://publications.waset.org/abstracts/search?q=semantic%20web%20application" title=" semantic web application"> semantic web application</a> </p> <a href="https://publications.waset.org/abstracts/11822/on-supporting-a-meta-design-approach-in-socio-technical-ontology-engineering" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11822.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">438</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">7318</span> Domain specific Ontology-Based Knowledge Extraction Using R-GNN and Large Language Models</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 proliferation of unstructured data in IT infrastructure management demands innovative approaches for extracting actionable knowledge. This paper presents a framework for ontology-based knowledge extraction that combines relational graph neural networks (R-GNN) with large language models (LLMs). The proposed method leverages the DOLCE framework as the foundational ontology, extending it with concepts from ITSMO for domain-specific applications in IT service management and outsourcing. A key component of this research is the use of transformer-based models, such as DeBERTa-v3-large, for automatic entity and relationship extraction from unstructured texts. Furthermore, the paper explores how transfer learning techniques can be applied to fine-tune large language models (LLaMA) for using to generate synthetic datasets to improve precision in BERT-based entity recognition and ontology alignment. The resulting IT Ontology (ITO) serves as a comprehensive knowledge base that integrates domain-specific insights from ITIL processes, enabling more efficient decision-making. Experimental results demonstrate significant improvements in knowledge extraction and relationship mapping, offering a cutting-edge solution for enhancing cognitive computing in IT service environments. <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=R-GNN" title=" R-GNN"> R-GNN</a>, <a href="https://publications.waset.org/abstracts/search?q=knowledge%20extraction" title=" knowledge extraction"> knowledge extraction</a>, <a href="https://publications.waset.org/abstracts/search?q=large%20language%20models" title=" large language models"> large language models</a>, <a href="https://publications.waset.org/abstracts/search?q=NER" title=" NER"> NER</a>, <a href="https://publications.waset.org/abstracts/search?q=knowlege%20graph" title=" knowlege graph"> knowlege graph</a> </p> <a href="https://publications.waset.org/abstracts/192578/domain-specific-ontology-based-knowledge-extraction-using-r-gnn-and-large-language-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/192578.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">16</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">7317</span> Facility Data Model as Integration and Interoperability Platform</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nikola%20Tomasevic">Nikola Tomasevic</a>, <a href="https://publications.waset.org/abstracts/search?q=Marko%20Batic"> Marko Batic</a>, <a href="https://publications.waset.org/abstracts/search?q=Sanja%20Vranes"> Sanja Vranes</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Emerging Semantic Web technologies can be seen as the next step in evolution of the intelligent facility management systems. Particularly, this considers increased usage of open source and/or standardized concepts for data classification and semantic interpretation. To deliver such facility management systems, providing the comprehensive integration and interoperability platform in from of the facility data model is a prerequisite. In this paper, one of the possible modelling approaches to provide such integrative facility data model which was based on the ontology modelling concept was presented. Complete ontology development process, starting from the input data acquisition, ontology concepts definition and finally ontology concepts population, was described. At the beginning, the core facility ontology was developed representing the generic facility infrastructure comprised of the common facility concepts relevant from the facility management perspective. To develop the data model of a specific facility infrastructure, first extension and then population of the core facility ontology was performed. For the development of the full-blown facility data models, Malpensa and Fiumicino airports in Italy, two major European air-traffic hubs, were chosen as a test-bed platform. Furthermore, the way how these ontology models supported the integration and interoperability of the overall airport energy management system was analyzed as well. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=airport%20ontology" title="airport ontology">airport ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=energy%20management" title=" energy management"> energy management</a>, <a href="https://publications.waset.org/abstracts/search?q=facility%20data%20model" title=" facility data model"> facility data model</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology%20modeling" title=" ontology modeling"> ontology modeling</a> </p> <a href="https://publications.waset.org/abstracts/21225/facility-data-model-as-integration-and-interoperability-platform" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21225.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">448</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">7316</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">7315</span> An Ontology for Investment in Chinese Steel Company</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Liming%20Chen">Liming Chen</a>, <a href="https://publications.waset.org/abstracts/search?q=Baoxin%20Xu"> Baoxin Xu</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhaoyun%20Ding"> Zhaoyun Ding</a>, <a href="https://publications.waset.org/abstracts/search?q=Bin%20Liu"> Bin Liu</a>, <a href="https://publications.waset.org/abstracts/search?q=Xianqiang%20Zhu"> Xianqiang Zhu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In the era of big data, public investors are faced with more complicated information related to investment decisions than ever before. To survive in the fierce competition, it has become increasingly urgent for investors to combine multi-source knowledge and evaluate the companies’ true value efficiently. For this, a rule-based ontology reasoning method is proposed to support steel companies’ value assessment. Considering the delay in financial disclosure and based on cost-benefit analysis, this paper introduces the supply chain enterprises financial analysis and constructs the ontology model used to value the value of steel company. In addition, domain knowledge is formally expressed with the help of Web Ontology Language (OWL) language and SWRL (Semantic Web Rule Language) rules. Finally, a case study on a steel company in China proved the effectiveness of the method we proposed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=financial%20ontology" title="financial ontology">financial ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=steel%20company" title=" steel company"> steel company</a>, <a href="https://publications.waset.org/abstracts/search?q=supply%20chain" title=" supply chain"> supply chain</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology%20reasoning" title=" ontology reasoning"> ontology reasoning</a> </p> <a href="https://publications.waset.org/abstracts/116477/an-ontology-for-investment-in-chinese-steel-company" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/116477.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">133</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">7314</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">7313</span> An Integrated Visualization Tool for Heat Map and Gene Ontology Graph</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Somyung%20Oh">Somyung Oh</a>, <a href="https://publications.waset.org/abstracts/search?q=Jeonghyeon%20Ha"> Jeonghyeon Ha</a>, <a href="https://publications.waset.org/abstracts/search?q=Kyungwon%20Lee"> Kyungwon Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Sejong%20Oh"> Sejong Oh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Microarray is a general scheme to find differentially expressed genes for target concept. The output is expressed by heat map, and biologists analyze related terms of gene ontology to find some characteristics of differentially expressed genes. In this paper, we propose integrated visualization tool for heat map and gene ontology graph. Previous two methods are used by static manner and separated way. Proposed visualization tool integrates them and users can interactively manage it. Users may easily find and confirm related terms of gene ontology for given differentially expressed genes. Proposed tool also visualize connections between genes on heat map and gene ontology graph. We expect biologists to find new meaningful topics by proposed tool. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=heat%20map" title="heat map">heat map</a>, <a href="https://publications.waset.org/abstracts/search?q=gene%20ontology" title=" gene ontology"> gene ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=microarray" title=" microarray"> microarray</a>, <a href="https://publications.waset.org/abstracts/search?q=differentially%20expressed%20gene" title=" differentially expressed gene"> differentially expressed gene</a> </p> <a href="https://publications.waset.org/abstracts/49151/an-integrated-visualization-tool-for-heat-map-and-gene-ontology-graph" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/49151.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">316</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=ontology%20learning&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=ontology%20learning&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=ontology%20learning&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=ontology%20learning&page=5">5</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=ontology%20learning&page=6">6</a></li> <li class="page-item"><a class="page-link" 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