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retrieval</title> <meta name="description" content="Search results for: thread retrieval"> <meta name="keywords" content="thread retrieval"> <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="thread retrieval"> <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> 405</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: thread retrieval</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">405</span> Leveraging Quality Metrics in Voting Model Based Thread Retrieval</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Atefeh%20Heydari">Atefeh Heydari</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammadali%20Tavakoli"> Mohammadali Tavakoli</a>, <a href="https://publications.waset.org/abstracts/search?q=Zuriati%20Ismail"> Zuriati Ismail</a>, <a href="https://publications.waset.org/abstracts/search?q=Naomie%20Salim"> Naomie Salim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Seeking and sharing knowledge on online forums have made them popular in recent years. Although online forums are valuable sources of information, due to variety of sources of messages, retrieving reliable threads with high quality content is an issue. Majority of the existing information retrieval systems ignore the quality of retrieved documents, particularly, in the field of thread retrieval. In this research, we present an approach that employs various quality features in order to investigate the quality of retrieved threads. Different aspects of content quality, including completeness, comprehensiveness, and politeness, are assessed using these features, which lead to finding not only textual, but also conceptual relevant threads for a user query within a forum. To analyse the influence of the features, we used an adopted version of voting model thread search as a retrieval system. We equipped it with each feature solely and also various combinations of features in turn during multiple runs. The results show that incorporating the quality features enhances the effectiveness of the utilised retrieval system significantly. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=content%20quality" title="content quality">content quality</a>, <a href="https://publications.waset.org/abstracts/search?q=forum%20search" title=" forum search"> forum search</a>, <a href="https://publications.waset.org/abstracts/search?q=thread%20retrieval" title=" thread retrieval"> thread retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=voting%20techniques" title=" voting techniques"> voting techniques</a> </p> <a href="https://publications.waset.org/abstracts/42749/leveraging-quality-metrics-in-voting-model-based-thread-retrieval" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/42749.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">213</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">404</span> Thread Lift: Classification, Technique, and How to Approach to the Patient</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Panprapa%20Yongtrakul">Panprapa Yongtrakul</a>, <a href="https://publications.waset.org/abstracts/search?q=Punyaphat%20Sirithanabadeekul"> Punyaphat Sirithanabadeekul</a>, <a href="https://publications.waset.org/abstracts/search?q=Pakjira%20Siriphan"> Pakjira Siriphan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: The thread lift technique has become popular because it is less invasive, requires a shorter operation, less downtime, and results in fewer postoperative complications. The advantage of the technique is that the thread can be inserted under the skin without the need for long incisions. Currently, there are a lot of thread lift techniques with respect to the specific types of thread used on specific areas, such as the mid-face, lower face, or neck area. Objective: To review the thread lift technique for specific areas according to type of thread, patient selection, and how to match the most appropriate to the patient. Materials and Methods: A literature review technique was conducted by searching PubMed and MEDLINE, then compiled and summarized. Result: We have divided our protocols into two sections: Protocols for short suture, and protocols for long suture techniques. We also created 3D pictures for each technique to enhance understanding and application in a clinical setting. Conclusion: There are advantages and disadvantages to short suture and long suture techniques. The best outcome for each patient depends on appropriate patient selection and determining the most suitable technique for the defect and area of patient concern. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=thread%20lift" title="thread lift">thread lift</a>, <a href="https://publications.waset.org/abstracts/search?q=thread%20lift%20method" title=" thread lift method"> thread lift method</a>, <a href="https://publications.waset.org/abstracts/search?q=thread%20lift%20technique" title=" thread lift technique"> thread lift technique</a>, <a href="https://publications.waset.org/abstracts/search?q=thread%20lift%20procedure" title=" thread lift procedure"> thread lift procedure</a>, <a href="https://publications.waset.org/abstracts/search?q=threading" title=" threading"> threading</a> </p> <a href="https://publications.waset.org/abstracts/53546/thread-lift-classification-technique-and-how-to-approach-to-the-patient" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/53546.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">263</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">403</span> The Pitch Diameter of Pipe Taper Thread Measurement and Uncertainty Using Three-Wire Probe</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=J.%20Kloypayan">J. Kloypayan</a>, <a href="https://publications.waset.org/abstracts/search?q=W.%20Pimpakan"> W. Pimpakan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The pipe taper thread measurement and uncertainty normally used the four-wire probe according to the JIS B 0262. Besides, according to the EA-10/10 standard, the pipe thread could be measured using the three-wire probe. This research proposed to use the three-wire probe measuring the pitch diameter of the pipe taper thread. The measuring accessory component was designed and made, then, assembled to one side of the ULM 828 CiM machine. Therefore, this machine could be used to measure and calibrate both the pipe thread and the pipe taper thread. The equations and the expanded uncertainty for pitch diameter measurement were formulated. After the experiment, the results showed that the pipe taper thread had the pitch diameter equal to 19.165 mm and the expanded uncertainty equal to 1.88µm. Then, the experiment results were compared to the results from the National Institute of Metrology Thailand. The equivalence ratio from the comparison showed that both results were related. Thus, the proposed method of using the three-wire probe measured the pitch diameter of the pipe taper thread was acceptable. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=pipe%20taper%20thread" title="pipe taper thread">pipe taper thread</a>, <a href="https://publications.waset.org/abstracts/search?q=three-wire%20probe" title=" three-wire probe"> three-wire probe</a>, <a href="https://publications.waset.org/abstracts/search?q=measure%20and%20calibration" title=" measure and calibration"> measure and calibration</a>, <a href="https://publications.waset.org/abstracts/search?q=the%20universal%20length%20measuring%20machine" title=" the universal length measuring machine"> the universal length measuring machine</a> </p> <a href="https://publications.waset.org/abstracts/2496/the-pitch-diameter-of-pipe-taper-thread-measurement-and-uncertainty-using-three-wire-probe" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2496.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">406</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">402</span> Performance Evaluation of Content Based Image Retrieval Using Indexed Views </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tahir%20Iqbal">Tahir Iqbal</a>, <a href="https://publications.waset.org/abstracts/search?q=Mumtaz%20Ali"> Mumtaz Ali</a>, <a href="https://publications.waset.org/abstracts/search?q=Syed%20Wajahat%20Kareem"> Syed Wajahat Kareem</a>, <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Harris"> Muhammad Harris </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Digital information is expanding in exponential order in our life. Information that is residing online and offline are stored in huge repositories relating to every aspect of our lives. Getting the required information is a task of retrieval systems. Content based image retrieval (CBIR) is a retrieval system that retrieves the required information from repositories on the basis of the contents of the image. Time is a critical factor in retrieval system and using indexed views with CBIR system improves the time efficiency of retrieved results. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=content%20based%20image%20retrieval%20%28CBIR%29" title="content based image retrieval (CBIR)">content based image retrieval (CBIR)</a>, <a href="https://publications.waset.org/abstracts/search?q=indexed%20view" title=" indexed view"> indexed view</a>, <a href="https://publications.waset.org/abstracts/search?q=color" title=" color"> color</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20retrieval" title=" image retrieval"> image retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=cross%20correlation" title=" cross correlation"> cross correlation</a> </p> <a href="https://publications.waset.org/abstracts/11165/performance-evaluation-of-content-based-image-retrieval-using-indexed-views" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11165.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">470</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">401</span> Eli-Twist Spun Yarn: An Alternative to Conventional Sewing Thread</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sujit%20Kumar%20Sinha">Sujit Kumar Sinha</a>, <a href="https://publications.waset.org/abstracts/search?q=Madan%20Lal%20Regar"> Madan Lal Regar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Sewing thread plays an important role in the transformation of a two-dimensional fabric into a three-dimensional garment. The interaction of the sewing thread with the fabric at the seam not only influences the appearance of a garment but also its performance. Careful selection of sewing thread and associated parameters can only help in improvement. Over the years, ring spinning has been dominating the yarn market. In the pursuit of improvement to challenge its dominance alternative technology has also been developed. But no real challenge has been posed by the any of the developed spinning systems. Eli-Twist spinning system can be a new method of yarn manufacture to provide a product with improved mechanical and physical properties with respect to the conventional ring spun yarn. The system, patented by Suessen has gained considerable attention in the recent times. The process of produces a two-ply compact yarn with improved fiber utilization. It produces a novel structure combining all advantages of condensing and doubling. In the present study, sewing threads of three different counts each from cotton, polyester and polyester/cotton (50/50) blend were produced on a ring and Eli-Twist systems. A twist multiplier of 4.2 was used to produce all the yarns. A comparison of hairiness, tensile strength and coefficient of friction with conventional ring yarn was made. Eli-Twist yarn has shown better frictional characteristics, better tensile strength and less hairiness. The performance of the Eli-Twist sewing thread has also been found to be better than the conventional 2-ply sewing thread. The performance was estimated through seam strength, seam elongation and seam efficiency of sewn fabric. Eli-Twist sewing thread has shown less friction, less hairiness, and higher tensile strength. Eli-Twist sewing thread resulted in better seam characteristics in comparison to conventional 2-ply sewing thread. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ring%20spun%20yarn" title="ring spun yarn">ring spun yarn</a>, <a href="https://publications.waset.org/abstracts/search?q=Eli-Twist%20yarn" title=" Eli-Twist yarn"> Eli-Twist yarn</a>, <a href="https://publications.waset.org/abstracts/search?q=sewing%20thread" title=" sewing thread"> sewing thread</a>, <a href="https://publications.waset.org/abstracts/search?q=seam%20strength" title=" seam strength"> seam strength</a>, <a href="https://publications.waset.org/abstracts/search?q=seam%20elongation" title=" seam elongation"> seam elongation</a>, <a href="https://publications.waset.org/abstracts/search?q=seam%20efficiency" title=" seam efficiency"> seam efficiency</a> </p> <a href="https://publications.waset.org/abstracts/84534/eli-twist-spun-yarn-an-alternative-to-conventional-sewing-thread" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/84534.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">400</span> Retrieval-Induced Forgetting Effects in Retrospective and Prospective Memory in Normal Aging: An Experimental Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Merve%20Akca">Merve Akca</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Retrieval-induced forgetting (RIF) refers to the phenomenon that selective retrieval of some information impairs memory for related, but not previously retrieved information. Despite age differences in retrieval-induced forgetting regarding retrospective memory being documented, this research aimed to highlight age differences in RIF of the prospective memory tasks for the first time. By using retrieval-practice paradigm, this study comparatively examined RIF effects in retrospective memory and event-based prospective memory in young and old adults. In this experimental study, a mixed factorial design with age group (Young, Old) as a between-subject variable, and memory type (Prospective, Retrospective) and item type (Practiced, Non-practiced) as within-subject variables was employed. Retrieval-induced forgetting was observed in the retrospective but not in the prospective memory task. Therefore, the results indicated that selective retrieval of past events led to suppression of other related past events in both age groups but not the suppression of memory for future intentions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=prospective%20memory" title="prospective memory">prospective memory</a>, <a href="https://publications.waset.org/abstracts/search?q=retrieval-induced%20forgetting" title=" retrieval-induced forgetting"> retrieval-induced forgetting</a>, <a href="https://publications.waset.org/abstracts/search?q=retrieval%20inhibition" title=" retrieval inhibition"> retrieval inhibition</a>, <a href="https://publications.waset.org/abstracts/search?q=retrospective%20memory" title=" retrospective memory"> retrospective memory</a> </p> <a href="https://publications.waset.org/abstracts/57915/retrieval-induced-forgetting-effects-in-retrospective-and-prospective-memory-in-normal-aging-an-experimental-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/57915.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> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">399</span> Information Retrieval for Kafficho Language</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mareye%20Zeleke%20Mekonen">Mareye Zeleke Mekonen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Kafficho language has distinct issues in information retrieval because of its restricted resources and dearth of standardized methods. In this endeavor, with the cooperation and support of linguists and native speakers, we investigate the creation of information retrieval systems specifically designed for the Kafficho language. The Kafficho information retrieval system allows Kafficho speakers to access information easily in an efficient and effective way. Our objective is to conduct an information retrieval experiment using 220 Kafficho text files, including fifteen sample questions. Tokenization, normalization, stop word removal, stemming, and other data pre-processing chores, together with additional tasks like term weighting, were prerequisites for the vector space model to represent each page and a particular query. The three well-known measurement metrics we used for our word were Precision, Recall, and and F-measure, with values of 87%, 28%, and 35%, respectively. This demonstrates how well the Kaffiho information retrieval system performed well while utilizing the vector space paradigm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kafficho" title="Kafficho">Kafficho</a>, <a href="https://publications.waset.org/abstracts/search?q=information%20retrieval" title=" information retrieval"> information retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=stemming" title=" stemming"> stemming</a>, <a href="https://publications.waset.org/abstracts/search?q=vector%20space" title=" vector space"> vector space</a> </p> <a href="https://publications.waset.org/abstracts/184199/information-retrieval-for-kafficho-language" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/184199.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">57</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">398</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">397</span> On the Role of Cutting Conditions on Surface Roughness in High-Speed Thread Milling of Brass C3600</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Amir%20Mahyar%20Khorasani">Amir Mahyar Khorasani</a>, <a href="https://publications.waset.org/abstracts/search?q=Ian%20Gibson"> Ian Gibson</a>, <a href="https://publications.waset.org/abstracts/search?q=Moshe%20Goldberg"> Moshe Goldberg</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Masoud%20Movahedi"> Mohammad Masoud Movahedi</a>, <a href="https://publications.waset.org/abstracts/search?q=Guy%20Littlefair"> Guy Littlefair</a> </p> <p class="card-text"><strong>Abstract:</strong></p> One of the important factors in manufacturing processes especially machining operations is surface quality. Improving this parameter results in improving fatigue strength, corrosion resistance, creep life and surface friction. The reliability and clearance of removable joints such as thread and nuts are highly related to the surface roughness. In this work, the effect of different cutting parameters such as cutting fluid pressure, feed rate and cutting speed on the surface quality of the crest of thread in the high-speed milling of Brass C3600 have been determined. Two popular neural networks containing MLP and RBF coupling with Taguchi L32 have been used to model surface roughness which was shown to be highly adept for such tasks. The contribution of this work is modelling surface roughness on the crest of the thread by using precise profilometer with nanoscale resolution. Experimental tests have been carried out for validation and approved suitable accuracy of the proposed model. Also analysing the interaction of parameters two by two showed that the most effective cutting parameter on the surface value is feed rate followed by cutting speed and cutting fluid pressure. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20neural%20networks" title="artificial neural networks">artificial neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=cutting%20conditions" title=" cutting conditions"> cutting conditions</a>, <a href="https://publications.waset.org/abstracts/search?q=high-speed%20machining" title=" high-speed machining"> high-speed machining</a>, <a href="https://publications.waset.org/abstracts/search?q=surface%20roughness" title=" surface roughness"> surface roughness</a>, <a href="https://publications.waset.org/abstracts/search?q=thread%20milling" title=" thread milling"> thread milling</a> </p> <a href="https://publications.waset.org/abstracts/46808/on-the-role-of-cutting-conditions-on-surface-roughness-in-high-speed-thread-milling-of-brass-c3600" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/46808.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">377</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">396</span> Comparison of Crossover Types to Obtain Optimal Queries Using Adaptive Genetic Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wafa%E2%80%99%20Alma%27Aitah">Wafa’ Alma'Aitah</a>, <a href="https://publications.waset.org/abstracts/search?q=Khaled%20Almakadmeh"> Khaled Almakadmeh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> this study presents an information retrieval system of using genetic algorithm to increase information retrieval efficiency. Using vector space model, information retrieval is based on the similarity measurement between query and documents. Documents with high similarity to query are judge more relevant to the query and should be retrieved first. Using genetic algorithms, each query is represented by a chromosome; these chromosomes are fed into genetic operator process: selection, crossover, and mutation until an optimized query chromosome is obtained for document retrieval. Results show that information retrieval with adaptive crossover probability and single point type crossover and roulette wheel as selection type give the highest recall. The proposed approach is verified using (242) proceedings abstracts collected from the Saudi Arabian national conference. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title="genetic algorithm">genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=information%20retrieval" title=" information retrieval"> information retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20queries" title=" optimal queries"> optimal queries</a>, <a href="https://publications.waset.org/abstracts/search?q=crossover" title=" crossover"> crossover</a> </p> <a href="https://publications.waset.org/abstracts/59109/comparison-of-crossover-types-to-obtain-optimal-queries-using-adaptive-genetic-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/59109.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">292</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">395</span> Content Based Face Sketch Images Retrieval in WHT, DCT, and DWT Transform Domain</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=W.%20S.%20Besbas">W. S. Besbas</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20A.%20Artemi"> M. A. Artemi</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20M.%20Salman"> R. M. Salman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Content based face sketch retrieval can be used to find images of criminals from their sketches for 'Crime Prevention'. This paper investigates the problem of CBIR of face sketch images in transform domain. Face sketch images that are similar to the query image are retrieved from the face sketch database. Features of the face sketch image are extracted in the spectrum domain of a selected transforms. These transforms are Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), and Walsh Hadamard Transform (WHT). For the performance analyses of features selection methods three face images databases are used. These are 'Sheffield face database', 'Olivetti Research Laboratory (ORL) face database', and 'Indian face database'. The City block distance measure is used to evaluate the performance of the retrieval process. The investigation concludes that, the retrieval rate is database dependent. But in general, the DCT is the best. On the other hand, the WHT is the best with respect to the speed of retrieving images. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Content%20Based%20Image%20Retrieval%20%28CBIR%29" title="Content Based Image Retrieval (CBIR)">Content Based Image Retrieval (CBIR)</a>, <a href="https://publications.waset.org/abstracts/search?q=face%20sketch%20image%20retrieval" title=" face sketch image retrieval"> face sketch image retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=features%20selection%20for%20CBIR" title=" features selection for CBIR"> features selection for CBIR</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20retrieval%20in%20transform%20domain" title=" image retrieval in transform domain"> image retrieval in transform domain</a> </p> <a href="https://publications.waset.org/abstracts/8251/content-based-face-sketch-images-retrieval-in-wht-dct-and-dwt-transform-domain" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/8251.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">493</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">394</span> A Verification Intellectual Property for Multi-Flow Rate Control on Any Single Flow Bus Functional Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pawamana%20Ramachandra">Pawamana Ramachandra</a>, <a href="https://publications.waset.org/abstracts/search?q=Jitesh%20Gupta"> Jitesh Gupta</a>, <a href="https://publications.waset.org/abstracts/search?q=Saranga%20P.%20Pogula"> Saranga P. Pogula</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In verification of high volume and complex packet processing IPs, finer control of flow management aspects (for example, rate, bits/sec etc.) per flow class (or a virtual channel or a software thread) is needed. When any Software/Universal Verification Methodology (UVM) thread arbitration is left to the simulator (e.g., Verilog Compiler Simulator (VCS) or Incisive Enterprise Simulator core simulation engine (NCSIM)), it is hard to predict its pattern of resulting distribution of bandwidth by the simulator thread arbitration. In many cases, the patterns desired in a test scenario may not be accomplished as the simulator might give a different distribution than what was required. This can lead to missing multiple traffic scenarios, specifically deadlock and starvation related. We invented a component (namely Flow Manager Verification IP) to be intervening between the application (test case) and the protocol VIP (with UVM sequencer) to control the bandwidth per thread/virtual channel/flow. The Flow Manager has knobs visible to the UVM sequence/test to configure the required distribution of rate per thread/virtual channel/flow. This works seamlessly and produces rate stimuli to further harness the Design Under Test (DUT) with asymmetric inputs compared to the programmed bandwidth/Quality of Service (QoS) distributions in the Design Under Test. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=flow%20manager" title="flow manager">flow manager</a>, <a href="https://publications.waset.org/abstracts/search?q=UVM%20sequencer" title=" UVM sequencer"> UVM sequencer</a>, <a href="https://publications.waset.org/abstracts/search?q=rated%20traffic%20generation" title=" rated traffic generation"> rated traffic generation</a>, <a href="https://publications.waset.org/abstracts/search?q=quality%20of%20service" title=" quality of service"> quality of service</a> </p> <a href="https://publications.waset.org/abstracts/168765/a-verification-intellectual-property-for-multi-flow-rate-control-on-any-single-flow-bus-functional-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/168765.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">99</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">393</span> Secure Image Retrieval Based on Orthogonal Decomposition under Cloud Environment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Y.%20Xu">Y. Xu</a>, <a href="https://publications.waset.org/abstracts/search?q=L.%20Xiong"> L. Xiong</a>, <a href="https://publications.waset.org/abstracts/search?q=Z.%20Xu"> Z. Xu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In order to protect data privacy, image with sensitive or private information needs to be encrypted before being outsourced to the cloud. However, this causes difficulties in image retrieval and data management. A secure image retrieval method based on orthogonal decomposition is proposed in the paper. The image is divided into two different components, for which encryption and feature extraction are executed separately. As a result, cloud server can extract features from an encrypted image directly and compare them with the features of the queried images, so that the user can thus obtain the image. Different from other methods, the proposed method has no special requirements to encryption algorithms. Experimental results prove that the proposed method can achieve better security and better retrieval precision. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=secure%20image%20retrieval" title="secure image retrieval">secure image retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=secure%20search" title=" secure search"> secure search</a>, <a href="https://publications.waset.org/abstracts/search?q=orthogonal%20decomposition" title=" orthogonal decomposition"> orthogonal decomposition</a>, <a href="https://publications.waset.org/abstracts/search?q=secure%20cloud%20computing" title=" secure cloud computing"> secure cloud computing</a> </p> <a href="https://publications.waset.org/abstracts/29115/secure-image-retrieval-based-on-orthogonal-decomposition-under-cloud-environment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/29115.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">485</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">392</span> Graph Codes - 2D Projections of Multimedia Feature Graphs for Fast and Effective Retrieval</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Stefan%20Wagenpfeil">Stefan Wagenpfeil</a>, <a href="https://publications.waset.org/abstracts/search?q=Felix%20Engel"> Felix Engel</a>, <a href="https://publications.waset.org/abstracts/search?q=Paul%20McKevitt"> Paul McKevitt</a>, <a href="https://publications.waset.org/abstracts/search?q=Matthias%20Hemmje"> Matthias Hemmje</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Multimedia Indexing and Retrieval is generally designed and implemented by employing feature graphs. These graphs typically contain a significant number of nodes and edges to reflect the level of detail in feature detection. A higher level of detail increases the effectiveness of the results but also leads to more complex graph structures. However, graph-traversal-based algorithms for similarity are quite inefficient and computation intensive, especially for large data structures. To deliver fast and effective retrieval, an efficient similarity algorithm, particularly for large graphs, is mandatory. Hence, in this paper, we define a graph-projection into a 2D space (Graph Code) as well as the corresponding algorithms for indexing and retrieval. We show that calculations in this space can be performed more efficiently than graph-traversals due to a simpler processing model and a high level of parallelization. In consequence, we prove that the effectiveness of retrieval also increases substantially, as Graph Codes facilitate more levels of detail in feature fusion. Thus, Graph Codes provide a significant increase in efficiency and effectiveness (especially for Multimedia indexing and retrieval) and can be applied to images, videos, audio, and text information. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=indexing" title="indexing">indexing</a>, <a href="https://publications.waset.org/abstracts/search?q=retrieval" title=" retrieval"> retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=multimedia" title=" multimedia"> multimedia</a>, <a href="https://publications.waset.org/abstracts/search?q=graph%20algorithm" title=" graph algorithm"> graph algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=graph%20code" title=" graph code"> graph code</a> </p> <a href="https://publications.waset.org/abstracts/135289/graph-codes-2d-projections-of-multimedia-feature-graphs-for-fast-and-effective-retrieval" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/135289.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">161</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">391</span> Unsupervised Domain Adaptive Text Retrieval with Query Generation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rui%20Yin">Rui Yin</a>, <a href="https://publications.waset.org/abstracts/search?q=Haojie%20Wang"> Haojie Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Xun%20Li"> Xun Li</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Recently, mainstream dense retrieval methods have obtained state-of-the-art results on some datasets and tasks. However, they require large amounts of training data, which is not available in most domains. The severe performance degradation of dense retrievers on new data domains has limited the use of dense retrieval methods to only a few domains with large training datasets. In this paper, we propose an unsupervised domain-adaptive approach based on query generation. First, a generative model is used to generate relevant queries for each passage in the target corpus, and then the generated queries are used for mining negative passages. Finally, the query-passage pairs are labeled with a cross-encoder and used to train a domain-adapted dense retriever. Experiments show that our approach is more robust than previous methods in target domains that require less unlabeled data. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=dense%20retrieval" title="dense retrieval">dense retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=query%20generation" title=" query generation"> query generation</a>, <a href="https://publications.waset.org/abstracts/search?q=unsupervised%20training" title=" unsupervised training"> unsupervised training</a>, <a href="https://publications.waset.org/abstracts/search?q=text%20retrieval" title=" text retrieval"> text retrieval</a> </p> <a href="https://publications.waset.org/abstracts/173903/unsupervised-domain-adaptive-text-retrieval-with-query-generation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/173903.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">73</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">390</span> Role of Natural Language Processing in Information Retrieval; Challenges and Opportunities </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Khaled%20M.%20Alhawiti">Khaled M. Alhawiti</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper aims to analyze the role of natural language processing (NLP). The paper will discuss the role in the context of automated data retrieval, automated question answer, and text structuring. NLP techniques are gaining wider acceptance in real life applications and industrial concerns. There are various complexities involved in processing the text of natural language that could satisfy the need of decision makers. This paper begins with the description of the qualities of NLP practices. The paper then focuses on the challenges in natural language processing. The paper also discusses major techniques of NLP. The last section describes opportunities and challenges for future research. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=data%20retrieval" title="data retrieval">data retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=information%20retrieval" title=" information retrieval"> information retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=natural%20language%20processing" title=" natural language processing"> natural language processing</a>, <a href="https://publications.waset.org/abstracts/search?q=text%20structuring" title=" text structuring"> text structuring</a> </p> <a href="https://publications.waset.org/abstracts/21284/role-of-natural-language-processing-in-information-retrieval-challenges-and-opportunities" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21284.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">340</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">389</span> Merging of Results in Distributed Information Retrieval Systems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Larbi%20Guezouli">Larbi Guezouli</a>, <a href="https://publications.waset.org/abstracts/search?q=Imane%20Azzouz"> Imane Azzouz</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This work is located in the domain of distributed information retrieval ‘DIR’. A simplified view of the DIR requires a multi-search in a set of collections, which forces the system to analyze results found in these collections, and merge results back before sending them to the user in a single list. Our work is to find a fusion method based on the relevance score of each result received from collections and the relevance of the local search engine of each collection. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=information%20retrieval" title="information retrieval">information retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=distributed%20IR%20systems" title=" distributed IR systems"> distributed IR systems</a>, <a href="https://publications.waset.org/abstracts/search?q=merging%20results" title=" merging results"> merging results</a>, <a href="https://publications.waset.org/abstracts/search?q=datamining" title=" datamining"> datamining</a> </p> <a href="https://publications.waset.org/abstracts/37130/merging-of-results-in-distributed-information-retrieval-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/37130.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">336</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">388</span> Content Based Video Retrieval System Using Principal Object Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Van%20Thinh%20Bui">Van Thinh Bui</a>, <a href="https://publications.waset.org/abstracts/search?q=Anh%20Tuan%20Tran"> Anh Tuan Tran</a>, <a href="https://publications.waset.org/abstracts/search?q=Quoc%20Viet%20Ngo"> Quoc Viet Ngo</a>, <a href="https://publications.waset.org/abstracts/search?q=The%20Bao%20Pham"> The Bao Pham</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Video retrieval is a searching problem on videos or clips based on content in which they are relatively close to an input image or video. The application of this retrieval consists of selecting video in a folder or recognizing a human in security camera. However, some recent approaches have been in challenging problem due to the diversity of video types, frame transitions and camera positions. Besides, that an appropriate measures is selected for the problem is a question. In order to overcome all obstacles, we propose a content-based video retrieval system in some main steps resulting in a good performance. From a main video, we process extracting keyframes and principal objects using Segmentation of Aggregating Superpixels (SAS) algorithm. After that, Speeded Up Robust Features (SURF) are selected from those principal objects. Then, the model “Bag-of-words” in accompanied by SVM classification are applied to obtain the retrieval result. Our system is performed on over 300 videos in diversity from music, history, movie, sports, and natural scene to TV program show. The performance is evaluated in promising comparison to the other approaches. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=video%20retrieval" title="video retrieval">video retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=principal%20objects" title=" principal objects"> principal objects</a>, <a href="https://publications.waset.org/abstracts/search?q=keyframe" title=" keyframe"> keyframe</a>, <a href="https://publications.waset.org/abstracts/search?q=segmentation%20of%20aggregating%20superpixels" title=" segmentation of aggregating superpixels"> segmentation of aggregating superpixels</a>, <a href="https://publications.waset.org/abstracts/search?q=speeded%20up%20robust%20features" title=" speeded up robust features"> speeded up robust features</a>, <a href="https://publications.waset.org/abstracts/search?q=bag-of-words" title=" bag-of-words"> bag-of-words</a>, <a href="https://publications.waset.org/abstracts/search?q=SVM" title=" SVM"> SVM</a> </p> <a href="https://publications.waset.org/abstracts/59753/content-based-video-retrieval-system-using-principal-object-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/59753.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">301</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">387</span> Local Texture and Global Color Descriptors for Content Based Image Retrieval</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tajinder%20Kaur">Tajinder Kaur</a>, <a href="https://publications.waset.org/abstracts/search?q=Anu%20Bala"> Anu Bala</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An image retrieval system is a computer system for browsing, searching, and retrieving images from a large database of digital images a new algorithm meant for content-based image retrieval (CBIR) is presented in this paper. The proposed method combines the color and texture features which are extracted the global and local information of the image. The local texture feature is extracted by using local binary patterns (LBP), which are evaluated by taking into consideration of local difference between the center pixel and its neighbors. For the global color feature, the color histogram (CH) is used which is calculated by RGB (red, green, and blue) spaces separately. In this paper, the combination of color and texture features are proposed for content-based image retrieval. The performance of the proposed method is tested on Corel 1000 database which is the natural database. The results after being investigated show a significant improvement in terms of their evaluation measures as compared to LBP and CH. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=color" title="color">color</a>, <a href="https://publications.waset.org/abstracts/search?q=texture" title=" texture"> texture</a>, <a href="https://publications.waset.org/abstracts/search?q=feature%20extraction" title=" feature extraction"> feature extraction</a>, <a href="https://publications.waset.org/abstracts/search?q=local%20binary%20patterns" title=" local binary patterns"> local binary patterns</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20retrieval" title=" image retrieval"> image retrieval</a> </p> <a href="https://publications.waset.org/abstracts/25503/local-texture-and-global-color-descriptors-for-content-based-image-retrieval" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/25503.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">366</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">386</span> A Graph-Based Retrieval Model for Passage Search</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Junjie%20Zhong">Junjie Zhong</a>, <a href="https://publications.waset.org/abstracts/search?q=Kai%20Hong"> Kai Hong</a>, <a href="https://publications.waset.org/abstracts/search?q=Lei%20Wang"> Lei Wang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Passage Retrieval (PR) plays an important role in many Natural Language Processing (NLP) tasks. Traditional efficient retrieval models relying on exact term-matching, such as TF-IDF or BM25, have nowadays been exceeded by pre-trained language models which match by semantics. Though they gain effectiveness, deep language models often require large memory as well as time cost. To tackle the trade-off between efficiency and effectiveness in PR, this paper proposes Graph Passage Retriever (GraphPR), a graph-based model inspired by the development of graph learning techniques. Different from existing works, GraphPR is end-to-end and integrates both term-matching information and semantics. GraphPR constructs a passage-level graph from BM25 retrieval results and trains a GCN-like model on the graph with graph-based objectives. Passages were regarded as nodes in the constructed graph and were embedded in dense vectors. PR can then be implemented using embeddings and a fast vector-similarity search. Experiments on a variety of real-world retrieval datasets show that the proposed model outperforms related models in several evaluation metrics (e.g., mean reciprocal rank, accuracy, F1-scores) while maintaining a relatively low query latency and memory usage. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=efficiency" title="efficiency">efficiency</a>, <a href="https://publications.waset.org/abstracts/search?q=effectiveness" title=" effectiveness"> effectiveness</a>, <a href="https://publications.waset.org/abstracts/search?q=graph%20learning" title=" graph learning"> graph learning</a>, <a href="https://publications.waset.org/abstracts/search?q=language%20model" title=" language model"> language model</a>, <a href="https://publications.waset.org/abstracts/search?q=passage%20retrieval" title=" passage retrieval"> passage retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=term-matching%20model" title=" term-matching model"> term-matching model</a> </p> <a href="https://publications.waset.org/abstracts/162229/a-graph-based-retrieval-model-for-passage-search" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/162229.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">150</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">385</span> Biomedical Definition Extraction Using Machine Learning with Synonymous Feature</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jian%20Qu">Jian Qu</a>, <a href="https://publications.waset.org/abstracts/search?q=Akira%20Shimazu"> Akira Shimazu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> OOV (Out Of Vocabulary) terms are terms that cannot be found in many dictionaries. Although it is possible to translate such OOV terms, the translations do not provide any real information for a user. We present an OOV term definition extraction method by using information available from the Internet. We use features such as occurrence of the synonyms and location distances. We apply machine learning method to find the correct definitions for OOV terms. We tested our method on both biomedical type and name type OOV terms, our work outperforms existing work with an accuracy of 86.5%. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=information%20retrieval" title="information retrieval">information retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=definition%20retrieval" title=" definition retrieval"> definition retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=OOV%20%28out%20of%20vocabulary%29" title=" OOV (out of vocabulary)"> OOV (out of vocabulary)</a>, <a href="https://publications.waset.org/abstracts/search?q=biomedical%20information%20retrieval" title=" biomedical information retrieval"> biomedical information retrieval</a> </p> <a href="https://publications.waset.org/abstracts/39665/biomedical-definition-extraction-using-machine-learning-with-synonymous-feature" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/39665.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">496</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">384</span> Domain Adaptive Dense Retrieval with Query Generation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rui%20Yin">Rui Yin</a>, <a href="https://publications.waset.org/abstracts/search?q=Haojie%20Wang"> Haojie Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Xun%20Li"> Xun Li</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Recently, mainstream dense retrieval methods have obtained state-of-the-art results on some datasets and tasks. However, they require large amounts of training data, which is not available in most domains. The severe performance degradation of dense retrievers on new data domains has limited the use of dense retrieval methods to only a few domains with large training datasets. In this paper, we propose an unsupervised domain-adaptive approach based on query generation. First, a generative model is used to generate relevant queries for each passage in the target corpus, and then, the generated queries are used for mining negative passages. Finally, the query-passage pairs are labeled with a cross-encoder and used to train a domain-adapted dense retriever. We also explore contrastive learning as a method for training domain-adapted dense retrievers and show that it leads to strong performance in various retrieval settings. Experiments show that our approach is more robust than previous methods in target domains that require less unlabeled data. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=dense%20retrieval" title="dense retrieval">dense retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=query%20generation" title=" query generation"> query generation</a>, <a href="https://publications.waset.org/abstracts/search?q=contrastive%20learning" title=" contrastive learning"> contrastive learning</a>, <a href="https://publications.waset.org/abstracts/search?q=unsupervised%20training" title=" unsupervised training"> unsupervised training</a> </p> <a href="https://publications.waset.org/abstracts/168338/domain-adaptive-dense-retrieval-with-query-generation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/168338.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">104</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">383</span> Strain Sensing Seams for Monitoring Body Movement</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sheilla%20Atieno%20Odhiambo">Sheilla Atieno Odhiambo</a>, <a href="https://publications.waset.org/abstracts/search?q=Simona%20Vasile"> Simona Vasile</a>, <a href="https://publications.waset.org/abstracts/search?q=Alexandra%20De%20Raeve"> Alexandra De Raeve</a>, <a href="https://publications.waset.org/abstracts/search?q=Ann%20Schwarz"> Ann Schwarz</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Strain sensing seams have been developed by integrating conductive sewing threads in different types of seams design on a fabric typical for sports clothing using sewing technology. The aim is to have a simple integrated textile strain sensor that can be applied to sports clothing to monitor the movements of the upper body parts of the user during sports. Different types of commercially available sewing threads were used as the bobbin thread in the production of different architectural seam sensors. These conductive sewing threads have been integrated into seams in particular designs using specific seam types. Some of the threads are delicate and needed to be laid into the seam with as little friction as possible and less tension; thus, they could only be sewn in as the bobbin thread and not the needle thread. Stitch type 304; 406; 506; 601;602; 605. were produced. The seams were made on a fabric of 80% polyamide 6.6 and 20% elastane. The seams were cycled(stretch-release-stretch) for five cycles and up to 44 cycles following EN ISO 14704-1: 2005 (modified), using a tensile instrument and the changes in the resistance of the seams with time were recorded using Agilent meter U1273A. Both experiments were conducted simultaneously on the same seam sample. Sensing functionality, among which is sensor gauge and reliability, were evaluated on the promising sensor seams. The results show that the sensor seams made from HC Madeira 40 conductive yarns performed better inseam stitch 304 and 602 compared to the other combination of stitch type and conductive sewing threads. These sensing seams 304, 406 and 602 will further be interconnected to our developed processing and communicating unit and further integrated into a sports clothing prototype that can track body posture. This research is done within the framework of the project SmartSeam. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=conductive%20sewing%20thread" title="conductive sewing thread">conductive sewing thread</a>, <a href="https://publications.waset.org/abstracts/search?q=sensing%20seams" title=" sensing seams"> sensing seams</a>, <a href="https://publications.waset.org/abstracts/search?q=smart%20seam" title=" smart seam"> smart seam</a>, <a href="https://publications.waset.org/abstracts/search?q=sewing%20technology" title=" sewing technology"> sewing technology</a> </p> <a href="https://publications.waset.org/abstracts/138619/strain-sensing-seams-for-monitoring-body-movement" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/138619.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">190</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">382</span> Case-Based Reasoning Approach for Process Planning of Internal Thread Cold Extrusion</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=D.%20Zhang">D. Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20Y.%20Du"> H. Y. Du</a>, <a href="https://publications.waset.org/abstracts/search?q=G.%20W.%20Li"> G. W. Li</a>, <a href="https://publications.waset.org/abstracts/search?q=J.%20Zeng"> J. Zeng</a>, <a href="https://publications.waset.org/abstracts/search?q=D.%20W.%20Zuo"> D. W. Zuo</a>, <a href="https://publications.waset.org/abstracts/search?q=Y.%20P.%20You"> Y. P. You</a> </p> <p class="card-text"><strong>Abstract:</strong></p> For the difficult issues of process selection, case-based reasoning technology is applied to computer aided process planning system for cold form tapping of internal threads on the basis of similarity in the process. A model is established based on the analysis of process planning. Case representation and similarity computing method are given. Confidence degree is used to evaluate the case. Rule-based reuse strategy is presented. The scheme is illustrated and verified by practical application. The case shows the design results with the proposed method are effective. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=case-based%20reasoning" title="case-based reasoning">case-based reasoning</a>, <a href="https://publications.waset.org/abstracts/search?q=internal%20thread" title=" internal thread"> internal thread</a>, <a href="https://publications.waset.org/abstracts/search?q=cold%20extrusion" title=" cold extrusion"> cold extrusion</a>, <a href="https://publications.waset.org/abstracts/search?q=process%20planning" title=" process planning"> process planning</a> </p> <a href="https://publications.waset.org/abstracts/20120/case-based-reasoning-approach-for-process-planning-of-internal-thread-cold-extrusion" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20120.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">510</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">381</span> Similarity Based Retrieval in Case Based Reasoning for Analysis of Medical Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Dasgupta">M. Dasgupta</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Banerjee"> S. Banerjee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Content Based Image Retrieval (CBIR) coupled with Case Based Reasoning (CBR) is a paradigm that is becoming increasingly popular in the diagnosis and therapy planning of medical ailments utilizing the digital content of medical images. This paper presents a survey of some of the promising approaches used in the detection of abnormalities in retina images as well in mammographic screening and detection of regions of interest in MRI scans of the brain. We also describe our proposed algorithm to detect hard exudates in fundus images of the retina of Diabetic Retinopathy patients. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=case%20based%20reasoning" title="case based reasoning">case based reasoning</a>, <a href="https://publications.waset.org/abstracts/search?q=exudates" title=" exudates"> exudates</a>, <a href="https://publications.waset.org/abstracts/search?q=retina%20image" title=" retina image"> retina image</a>, <a href="https://publications.waset.org/abstracts/search?q=similarity%20based%20retrieval" title=" similarity based retrieval"> similarity based retrieval</a> </p> <a href="https://publications.waset.org/abstracts/2992/similarity-based-retrieval-in-case-based-reasoning-for-analysis-of-medical-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2992.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">348</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">380</span> A Framework of Product Information Service System Using Mobile Image Retrieval and Text Mining Techniques</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mei-Yi%20Wu">Mei-Yi Wu</a>, <a href="https://publications.waset.org/abstracts/search?q=Shang-Ming%20Huang"> Shang-Ming Huang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The online shoppers nowadays often search the product information on the Internet using some keywords of products. To use this kind of information searching model, shoppers should have a preliminary understanding about their interesting products and choose the correct keywords. However, if the products are first contact (for example, the worn clothes or backpack of passengers which you do not have any idea about the brands), these products cannot be retrieved due to insufficient information. In this paper, we discuss and study the applications in E-commerce using image retrieval and text mining techniques. We design a reasonable E-commerce application system containing three layers in the architecture to provide users product information. The system can automatically search and retrieval similar images and corresponding web pages on Internet according to the target pictures which taken by users. Then text mining techniques are applied to extract important keywords from these retrieval web pages and search the prices on different online shopping stores with these keywords using a web crawler. Finally, the users can obtain the product information including photos and prices of their favorite products. The experiments shows the efficiency of proposed system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=mobile%20image%20retrieval" title="mobile image retrieval">mobile image retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=text%20mining" title=" text mining"> text mining</a>, <a href="https://publications.waset.org/abstracts/search?q=product%20information%20service%20system" title=" product information service system"> product information service system</a>, <a href="https://publications.waset.org/abstracts/search?q=online%20marketing" title=" online marketing"> online marketing</a> </p> <a href="https://publications.waset.org/abstracts/33483/a-framework-of-product-information-service-system-using-mobile-image-retrieval-and-text-mining-techniques" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/33483.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">359</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">379</span> Selection of Relevant Servers in Distributed Information Retrieval System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Benhamouda%20Sara">Benhamouda Sara</a>, <a href="https://publications.waset.org/abstracts/search?q=Guezouli%20Larbi"> Guezouli Larbi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Nowadays, the dissemination of information touches the distributed world, where selecting the relevant servers to a user request is an important problem in distributed information retrieval. During the last decade, several research studies on this issue have been launched to find optimal solutions and many approaches of collection selection have been proposed. In this paper, we propose a new collection selection approach that takes into consideration the number of documents in a collection that contains terms of the query and the weights of those terms in these documents. We tested our method and our studies show that this technique can compete with other state-of-the-art algorithms that we choose to test the performance of our approach. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=distributed%20information%20retrieval" title="distributed information retrieval">distributed information retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=relevance" title=" relevance"> relevance</a>, <a href="https://publications.waset.org/abstracts/search?q=server%20selection" title=" server selection"> server selection</a>, <a href="https://publications.waset.org/abstracts/search?q=collection%20selection" title=" collection selection"> collection selection</a> </p> <a href="https://publications.waset.org/abstracts/37133/selection-of-relevant-servers-in-distributed-information-retrieval-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/37133.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">378</span> Algorithm for Information Retrieval Optimization</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kehinde%20K.%20Agbele">Kehinde K. Agbele</a>, <a href="https://publications.waset.org/abstracts/search?q=Kehinde%20Daniel%20Aruleba"> Kehinde Daniel Aruleba</a>, <a href="https://publications.waset.org/abstracts/search?q=Eniafe%20F.%20Ayetiran"> Eniafe F. Ayetiran</a> </p> <p class="card-text"><strong>Abstract:</strong></p> When using Information Retrieval Systems (IRS), users often present search queries made of ad-hoc keywords. It is then up to the IRS to obtain a precise representation of the user’s information need and the context of the information. This paper investigates optimization of IRS to individual information needs in order of relevance. The study addressed development of algorithms that optimize the ranking of documents retrieved from IRS. This study discusses and describes a Document Ranking Optimization (DROPT) algorithm for information retrieval (IR) in an Internet-based or designated databases environment. Conversely, as the volume of information available online and in designated databases is growing continuously, ranking algorithms can play a major role in the context of search results. In this paper, a DROPT technique for documents retrieved from a corpus is developed with respect to document index keywords and the query vectors. This is based on calculating the weight ( <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=information%20retrieval" title="information retrieval">information retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=document%20relevance" title=" document relevance"> document relevance</a>, <a href="https://publications.waset.org/abstracts/search?q=performance%20measures" title=" performance measures"> performance measures</a>, <a href="https://publications.waset.org/abstracts/search?q=personalization" title=" personalization"> personalization</a> </p> <a href="https://publications.waset.org/abstracts/40905/algorithm-for-information-retrieval-optimization" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/40905.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">241</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">377</span> Content-Based Image Retrieval Using HSV Color Space Features</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hamed%20Qazanfari">Hamed Qazanfari</a>, <a href="https://publications.waset.org/abstracts/search?q=Hamid%20Hassanpour"> Hamid Hassanpour</a>, <a href="https://publications.waset.org/abstracts/search?q=Kazem%20Qazanfari"> Kazem Qazanfari</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a method is provided for content-based image retrieval. Content-based image retrieval system searches query an image based on its visual content in an image database to retrieve similar images. In this paper, with the aim of simulating the human visual system sensitivity to image's edges and color features, the concept of color difference histogram (CDH) is used. CDH includes the perceptually color difference between two neighboring pixels with regard to colors and edge orientations. Since the HSV color space is close to the human visual system, the CDH is calculated in this color space. In addition, to improve the color features, the color histogram in HSV color space is also used as a feature. Among the extracted features, efficient features are selected using entropy and correlation criteria. The final features extract the content of images most efficiently. The proposed method has been evaluated on three standard databases Corel 5k, Corel 10k and UKBench. Experimental results show that the accuracy of the proposed image retrieval method is significantly improved compared to the recently developed methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=content-based%20image%20retrieval" title="content-based image retrieval">content-based image retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=color%20difference%20histogram" title=" color difference histogram"> color difference histogram</a>, <a href="https://publications.waset.org/abstracts/search?q=efficient%20features%20selection" title=" efficient features selection"> efficient features selection</a>, <a href="https://publications.waset.org/abstracts/search?q=entropy" title=" entropy"> entropy</a>, <a href="https://publications.waset.org/abstracts/search?q=correlation" title=" correlation"> correlation</a> </p> <a href="https://publications.waset.org/abstracts/75068/content-based-image-retrieval-using-hsv-color-space-features" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/75068.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">249</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">376</span> Urdu Text Extraction Method from Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Samabia%20Tehsin">Samabia Tehsin</a>, <a href="https://publications.waset.org/abstracts/search?q=Sumaira%20Kausar"> Sumaira Kausar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Due to the vast increase in the multimedia data in recent years, efficient and robust retrieval techniques are needed to retrieve and index images/ videos. Text embedded in the images can serve as the strong retrieval tool for images. This is the reason that text extraction is an area of research with increasing attention. English text extraction is the focus of many researchers but very less work has been done on other languages like Urdu. This paper is focusing on Urdu text extraction from video frames. This paper presents a text detection feature set, which has the ability to deal up with most of the problems connected with the text extraction process. To test the validity of the method, it is tested on Urdu news dataset, which gives promising results. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=caption%20text" title="caption text">caption text</a>, <a href="https://publications.waset.org/abstracts/search?q=content-based%20image%20retrieval" title=" content-based image retrieval"> content-based image retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=document%20analysis" title=" document analysis"> document analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=text%20extraction" title=" text extraction"> text extraction</a> </p> <a href="https://publications.waset.org/abstracts/9566/urdu-text-extraction-method-from-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9566.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">516</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=thread%20retrieval&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=thread%20retrieval&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=thread%20retrieval&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=thread%20retrieval&page=5">5</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=thread%20retrieval&page=6">6</a></li> <li class="page-item"><a class="page-link" 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