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Dissertations / Theses on the topic 'Latent semantic analysis (LSA)'

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1

Makovoz, Gennadiy. "Latent Semantic Analysis as a Method of Content-Based Image Retrieval in Medical Applications." NSUWorks, 2010. http://nsuworks.nova.edu/gscis_etd/227.

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The research investigated whether a Latent Semantic Analysis (LSA)-based approach to image retrieval can map pixel intensity into a smaller concept space with good accuracy and reasonable computational cost. From a large set of computed tomography (CT) images, a retrieval query found all images for a particular patient based on semantic similarity. The effectiveness of the LSA retrieval was evaluated based on precision, recall, and F-score. This work extended the application of LSA to high-resolution CT radiology images. The images were chosen for their unique characteristics and their importa
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Natividad, Beltrán del Río Gloria Ofelia. "An Analysis of Educational Technology Publications: Who, What and Where in the Last 20 Years." Thesis, University of North Texas, 2016. https://digital.library.unt.edu/ark:/67531/metadc849761/.

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This exploratory and descriptive study examines research articles published in ten of the top journals in the broad area of educational technology during the last 20 years: 1) Educational Technology Research and Development (ETR&D); 2) Instructional Science; 3) Journal of the Learning Sciences; 4) TechTrends; 5) Educational Technology: The Magazine for Managers of Change in Education; 6) Journal of Educational Technology & Society; 7) Computers and Education; 8) British Journal of Educational Technology (BJET); 9) Journal of Educational Computing Research; and 10) Journal of Research on Techno
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Hossain, Muhammad Muazzem. "Investigating the relationship between the business performance management framework and the Malcolm Baldrige National Quality Award framework." Thesis, University of North Texas, 2009. https://digital.library.unt.edu/ark:/67531/metadc11034/.

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The business performance management (BPM) framework helps an organization continuously adjust and successfully execute its strategies. BPM helps increase flexibility by providing managers with an early alert about changes and, as a result, allows faster response to such changes. The Malcolm Baldrige National Quality Award (MBNQA) framework provides a basis for self-assessment and a systems perspective for managing an organization's key processes for achieving business results. The MBNQA framework is a more comprehensive framework and encapsulates the underlying constructs in the BPM framework.
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SANTOS, João Carlos Alves dos. "Avaliação automática de questões discursivas usando LSA." Universidade Federal do Pará, 2016. http://repositorio.ufpa.br/jspui/handle/2011/7485.

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Submitted by camilla martins (camillasmmartins@gmail.com) on 2017-01-27T15:50:37Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Tese_AvaliacaoAutomaticaQuestoes.pdf: 5106074 bytes, checksum: c401d50ce5e666c52948ece7af20b2c3 (MD5)<br>Approved for entry into archive by Edisangela Bastos (edisangela@ufpa.br) on 2017-01-30T13:02:31Z (GMT) No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Tese_AvaliacaoAutomaticaQuestoes.pdf: 5106074 bytes, checksum: c401d50ce5e666c52948ece7af20b2c3 (MD5)<br>Made available
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Kučaidze, Artiom. "Tinklalapio navigavimo asociacijų analizės ir prognozavimo modelis." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2009. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2008~D_20090908_201802-74260.

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Darbe, remiantis informacijos paieškos teorija, bandoma sukurti tinklalapio navigavimo asociacijų analizės ir prognozavimo modelį. Šio modelio tikslas – simuliuoti potencialių tinklalapio vartotojų informacijos paieškos kelius turint apibrėžtą informacinį tikslą. Modelis kuriamas apjungiant LSA, SVD algoritmus ir koreliacijos koeficientų skaičiavimus. LSA algoritmas naudojamas kuriant semantines erdves, o koreliacijos koeficientų skaičiavimai naudojami statistikoje. Kartu jie leidžia tinklalapio navigavimo asociacijų analizės ir prognozavimo modeliui analizuoti žodžių semantinį panašumą. Darbo
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6

Belica, Michal. "Metody sumarizace dokumentů na webu." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2013. http://www.nusl.cz/ntk/nusl-236386.

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The work deals with automatic summarization of documents in HTML format. As a language of web documents, Czech language has been chosen. The project is focused on algorithms of text summarization. The work also includes document preprocessing for summarization and conversion of text into representation suitable for summarization algorithms. General text mining is also briefly discussed but the project is mainly focused on the automatic document summarization. Two simple summarization algorithms are introduced. Then, the main attention is paid to an advanced algorithm that uses latent semantic
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Ozsoy, Makbule Gulcin. "Text Summarization Using Latent Semantic Analysis." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12612988/index.pdf.

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Text summarization solves the problem of presenting the information needed by a user in a compact form. There are different approaches to create well formed summaries in literature. One of the newest methods in text summarization is the Latent Semantic Analysis (LSA) method. In this thesis, different LSA based summarization algorithms are explained and two new LSA based summarization algorithms are proposed. The algorithms are evaluated on Turkish and English documents, and their performances are compared using their ROUGE scores.
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Anaya, Leticia H. "Comparing Latent Dirichlet Allocation and Latent Semantic Analysis as Classifiers." Thesis, University of North Texas, 2011. https://digital.library.unt.edu/ark:/67531/metadc103284/.

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In the Information Age, a proliferation of unstructured text electronic documents exists. Processing these documents by humans is a daunting task as humans have limited cognitive abilities for processing large volumes of documents that can often be extremely lengthy. To address this problem, text data computer algorithms are being developed. Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA) are two text data computer algorithms that have received much attention individually in the text data literature for topic extraction studies but not for document classification nor for
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9

Huang, Fang. "Multi-document summarization with latent semantic analysis." Thesis, University of Sheffield, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.419255.

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Buys, Stephanus. "Log analysis aided by latent semantic mapping." Thesis, Rhodes University, 2013. http://hdl.handle.net/10962/d1002963.

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In an age of zero-day exploits and increased on-line attacks on computing infrastructure, operational security practitioners are becoming increasingly aware of the value of the information captured in log events. Analysis of these events is critical during incident response, forensic investigations related to network breaches, hacking attacks and data leaks. Such analysis has led to the discipline of Security Event Analysis, also known as Log Analysis. There are several challenges when dealing with events, foremost being the increased volumes at which events are often generated and stored. Fur
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Favre, Benoit. "Résumé automatique de parole pour un accès efficace aux bases de données audio." Phd thesis, Université d'Avignon, 2007. http://tel.archives-ouvertes.fr/tel-00444105.

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L'avènement du numérique permet de stocker de grandes quantités de parole à moindre coût. Malgré les récentes avancées en recherche documentaire audio, il reste difficile d'exploiter les documents à cause du temps nécessaire pour les écouter. Nous tentons d'atténuer cet inconvénient en produisant un résumé automatique parlé à partir des informations les plus importantes. Pour y parvenir, une méthode de résumé par extraction est appliquée au contenu parlé, transcrit et structuré automatiquement. La transcription enrichie est réalisée grâce aux outils Speeral et Alize développés au LIA. Nous com
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Lin, Sheng-Ting. "Latent semantic analysis for retrieving related biomedical articles." Thesis, University of British Columbia, 2017. http://hdl.handle.net/2429/61273.

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Retrieving relevant scientific papers in a scalable way is increasingly important, as more and more studies are published. PubMed’s relevant article recommendation is based on MeSH assignments by indexers, which requires significant human resources and can become a limitation in making papers searchable. Many recommendation systems use singular value decomposition (SVD) to pre-compute related products. In this study, we look at using latent semantic analysis (LSA), an application of SVD to determine relationships in a set of documents and terms, to find related biomedical papers. We focused on
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Stone, Andrew John William. "Performing pre-requirements tracing using latent semantic analysis." Thesis, Lancaster University, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.497169.

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Requirements tracing is a universally neglected practice in industry, despite clear knowledgement that it supports high-end practices, such as change management and control and impact analysis. Requirements tracing is comprised of two principal types; pre- and post-requirement specification tracing. Post-requirement.specificadon tracing, or post-RST, is concerned with tracing requirements after they have already bncluded in the specification. Pre-RST is concerned with life before inclusion, and therefore represents the origin of each requirement. Pre-RST is less often implemented in practice t
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MENDONCA, DIOGO SILVEIRA. "PROBABILISTIC LATENT SEMANTIC ANALYSIS APPLIED TO RECOMMENDER SYSTEMS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2008. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=13073@1.

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Os sistemas de recomendação são um tema de pesquisa constante devido a sua grande quantidade de aplicações práticas. Estes sistemas podem ser abordados de diversas maneiras, sendo uma das mais utilizadas a filtragem colaborativa, em que para recomendar um item a um usuário são utilizados dados de comportamento de outros usuários. Porém, nem sempre os algoritmos de filtragem colaborativa atingem níveis de precisão necessários para serem utilizados em aplicações reais. Desta forma este trabalho tem como objetivo avaliar o desempenho da análise probabilística de semântica latente (PLSA) aplicado
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Akther, Aysha. "Social Tag-based Community Recommendation Using Latent Semantic Analysis." Thèse, Université d'Ottawa / University of Ottawa, 2012. http://hdl.handle.net/10393/23238.

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Collaboration and sharing of information are the basis of modern social web system. Users in the social web systems are establishing and joining online communities, in order to collectively share their content with a group of people having common topic of interest. Group or community activities have increased exponentially in modern social Web systems. With the explosive growth of social communities, users of social Web systems have experienced considerable difficulty with discovering communities relevant to their interests. In this study, we address the problem of recommending communities to
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16

Sheikha, Hassan. "Text mining Twitter social media for Covid-19 : Comparing latent semantic analysis and latent Dirichlet allocation." Thesis, Högskolan i Gävle, Avdelningen för datavetenskap och samhällsbyggnad, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-32567.

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In this thesis, the Twitter social media is data mined for information about the covid-19 outbreak during the month of March, starting from the 3’rd and ending on the 31’st. 100,000 tweets were collected from Harvard’s opensource data and recreated using Hydrate. This data is analyzed further using different Natural Language Processing (NLP) methodologies, such as termfrequency inverse document frequency (TF-IDF), lemmatizing, tokenizing, Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA). Furthermore, the results of the LSA and LDA algorithms is reduced dimensional data that
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Arroniz, Inigo. "EXTRACTING QUANTITATIVE INFORMATIONFROM NONNUMERIC MARKETING DATA: AN AUGMENTEDLATENT SEMANTIC ANALYSIS APPROACH." Doctoral diss., University of Central Florida, 2007. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3083.

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Despite the widespread availability and importance of nonnumeric data, marketers do not have the tools to extract information from large amounts of nonnumeric data. This dissertation attempts to fill this void: I developed a scalable methodology that is capable of extracting information from extremely large volumes of nonnumeric data. The proposed methodology integrates concepts from information retrieval and content analysis to analyze textual information. This approach avoids a pervasive difficulty of traditional content analysis, namely the classification of terms into predetermined categor
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Eryol, Erkin. "Probabilistic Latent Semantic Analysis Based Framework For Hybrid Social Recommender Systems." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/2/12611921/index.pdf.

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Today, there are user annotated internet sites, user interaction logs, online user communities which are valuable sources of information concerning the personalized recommendation problem. In the literature, hybrid social recommender systems have been proposed to reduce the sparsity of the usage data by integrating the user related information sources together. In this thesis, a method based on probabilistic latent semantic analysis is used as a framework for a hybrid social recommendation system. Different data hybridization approaches on probabilistic latent semantic analysis are experimente
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Mrva, David. "The use of probabilistic latent semantic analysis in adaptive language models." Thesis, University of Cambridge, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.611121.

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Coccaro, Noah B. "Latent semantic analysis as a tool to improve automatic speech recognition performance." Diss., Connect to online resource, 2005. http://wwwlib.umi.com/cr/colorado/fullcit?p3190360.

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Cosma, Georgina. "An approach to source-code plagiarism detection investigation using latent semantic analysis." Thesis, University of Warwick, 2008. http://wrap.warwick.ac.uk/3575/.

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This thesis looks at three aspects of source-code plagiarism. The first aspect of the thesis is concerned with creating a definition of source-code plagiarism; the second aspect is concerned with describing the findings gathered from investigating the Latent Semantic Analysis information retrieval algorithm for source-code similarity detection; and the final aspect of the thesis is concerned with the proposal and evaluation of a new algorithm that combines Latent Semantic Analysis with plagiarism detection tools. A recent review of the literature revealed that there is no commonly agreed defin
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Spomer, Judith E. "Latent semantic analysis and classification modeling in applications for social movement theory /." Abstract Full Text (HTML) Full Text (PDF), 2008. http://eprints.ccsu.edu/archive/00000552/02/1996FT.htm.

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Thesis (M.S.) -- Central Connecticut State University, 2008.<br>Thesis advisor: Roger Bilisoly. "... in partial fulfillment of the requirements for the degree of Master of Science in Data Mining." Includes bibliographical references (leaves 122-127). Also available via the World Wide Web.
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Scalzo, Gabriella C. "Using Latent Semantic Analysis to Evaluate the Coherence of Traumatic Event Narratives." VCU Scholars Compass, 2019. https://scholarscompass.vcu.edu/etd/5802.

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While a growing evidence base suggests that expressive writing about a traumatic event may be an effective intervention which results in a variety of health benefits, there are still multiple competing theories that seek to explain expressive writing’s mechanism(s) of action. Two of the theories with stronger evidence bases are exposure theory and cognitive processing theory. The state of this field is complicated by methodological limitations; operationalizing and measuring the relative constructs of trauma narratives, such as coherence, traditionally requires time- and labor-intensive method
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Elsas, Jonathan L. "An Evaluation of Projection Techniques for Document Clustering: Latent Semantic Analysis and Independent Component Analysis." Thesis, School of Information and Library Science, 2005. http://hdl.handle.net/1901/208.

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Dimensionality reduction in the bag-of-words vector space document representation model has been widely studied for the purposes of improving accuracy and reducing computational load of document retrieval tasks. These techniques, however, have not been studied to the same degree with regard to document clustering tasks. This study evaluates the effectiveness of two popular dimensionality reduction techniques for clustering, and their effect on discovering accurate and understandable topical groupings of documents. The two techniques studied are Latent Semantic Analysis and Independent Compo
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Hassan, Samer. "Measuring Semantic Relatedness Using Salient Encyclopedic Concepts." Thesis, University of North Texas, 2011. https://digital.library.unt.edu/ark:/67531/metadc84212/.

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While pragmatics, through its integration of situational awareness and real world relevant knowledge, offers a high level of analysis that is suitable for real interpretation of natural dialogue, semantics, on the other end, represents a lower yet more tractable and affordable linguistic level of analysis using current technologies. Generally, the understanding of semantic meaning in literature has revolved around the famous quote ``You shall know a word by the company it keeps''. In this thesis we investigate the role of context constituents in decoding the semantic meaning of the engulfing
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Dietl, Reinhard. "A Reference Architecture for Providing Latent Semantic Analysis Applications in Distributed Systems. Diploma Thesis." WU Vienna University of Economics and Business, 2010. http://epub.wu.ac.at/3016/1/EPUB_Thesis_Dietl.pdf.

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With the increasing availability of storage and computing power, Latent Semantic Analysis (LSA) has gained more and more significance in practice over the last decade. This diploma thesis aims to develop a reference architecture which can be utilised to provide LSA based applications in a distributed system. It outlines the underlying problems of generation, processing and storage of large data objects resulting from LSA operations, the problems arising from bringing LSA into a distributed context, suggests an architecture for the software components necessary to perform the tasks, and evaluat
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Polyakov, Serhiy. "Enhancing User Search Experience in Digital Libraries with Rotated Latent Semantic Indexing." Thesis, University of North Texas, 2015. https://digital.library.unt.edu/ark:/67531/metadc804881/.

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This study investigates a semi-automatic method for creation of topical labels representing the topical concepts in information objects. The method is called rotated latent semantic indexing (rLSI). rLSI has found application in text mining but has not been used for topical labels generation in digital libraries (DLs). The present study proposes a theoretical model and an evaluation framework which are based on the LSA theory of meaning and investigates rLSI in a DL environment. The proposed evaluation framework for rLSI topical labels is focused on human-information search behavior and satisf
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Ashton, Triss A. "Accuracy and Interpretability Testing of Text Mining Methods." Thesis, University of North Texas, 2013. https://digital.library.unt.edu/ark:/67531/metadc283791/.

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Extracting meaningful information from large collections of text data is problematic because of the sheer size of the database. However, automated analytic methods capable of processing such data have emerged. These methods, collectively called text mining first began to appear in 1988. A number of additional text mining methods quickly developed in independent research silos with each based on unique mathematical algorithms. How good each of these methods are at analyzing text is unclear. Method development typically evolves from some research silo centric requirement with the success of
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Shen, Yao. "Scene Analysis Using Scale Invariant Feature Extraction and Probabilistic Modeling." Thesis, University of North Texas, 2011. https://digital.library.unt.edu/ark:/67531/metadc84275/.

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Conventional pattern recognition systems have two components: feature analysis and pattern classification. For any object in an image, features could be considered as the major characteristic of the object either for object recognition or object tracking purpose. Features extracted from a training image, can be used to identify the object when attempting to locate the object in a test image containing many other objects. To perform reliable scene analysis, it is important that the features extracted from the training image are detectable even under changes in image scale, noise and illuminatio
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Zaras, Dimitrios. "Evaluating Semantic Internalization Among Users of an Online Review Platform." Thesis, University of North Texas, 2015. https://digital.library.unt.edu/ark:/67531/metadc804823/.

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The present study draws on recent sociological literature that argues that the study of cognition and culture can benefit from theories of embodied cognition. The concept of semantic internalization is introduced, which is conceptualized as the ability to perceive and articulate the topics that are of most concern to a community as they are manifested in social discourse. Semantic internalization is partly an application of emotional intelligence in the context of community-level discourse. Semantic internalization is measured through the application of Latent Semantic Analysis. Furthermore, i
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Karlsson, Kristina. "Semantic represenations of retrieved memory information depend on cue-modality." Thesis, Stockholms universitet, Psykologiska institutionen, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-58817.

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The semantic content (i.e., meaning of words) is the essence of retrieved autobiographical memories. In comparison to previous research, which has mainly focused on phenomenological experiences and age distribution of memory events, the present study provides a novel view on the retrieval of event information by addressing the semantic representation of memories. In the present study the semantic representation (i.e., word locations represented by vectors in a high dimensional space) of retrieved memory information were investigated, by analyzing the data with an automatic statistical algorith
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Chen, Xin. "Human-centered semantic retrieval in multimedia databases." Birmingham, Ala. : University of Alabama at Birmingham, 2008. https://www.mhsl.uab.edu/dt/2008p/chen.pdf.

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Thesis (Ph. D.)--University of Alabama at Birmingham, 2008.<br>Additional advisors: Barrett R. Bryant, Yuhua Song, Alan Sprague, Robert W. Thacker. Description based on contents viewed Oct. 8, 2008; title from PDF t.p. Includes bibliographical references (p. 172-183).
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Haley, Debra. "Applying latent semantic analysis to computer assisted assessment in the Computer Science domain : a framework, a tool, and an evaluation." Thesis, Open University, 2009. http://oro.open.ac.uk/25955/.

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This dissertation argues that automated assessment systems can be useful for both students and educators provided that the results correspond well with human markers. Thus, evaluating such a system is crucial. I present an evaluation framework and show how and why it can be useful for both producers and consumers of automated assessment systems. The framework is a refinement of a research taxonomy that came out of the effort to analyse the literature review of systems based on Latent Semantic Analysis (LSA), a statistical natural language processing technique that has been used for automated a
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Al, Batineh Mohammed S. "Latent Semantic Analysis, Corpus stylistics and Machine Learning Stylometry for Translational and Authorial Style Analysis: The Case of Denys Johnson-Davies’ Translations into English." Kent State University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=kent1429300641.

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Bose, Aishwarya. "Effective web service discovery using a combination of a semantic model and a data mining technique." Thesis, Queensland University of Technology, 2008. https://eprints.qut.edu.au/26425/1/Aishwarya_Bose_Thesis.pdf.

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With the advent of Service Oriented Architecture, Web Services have gained tremendous popularity. Due to the availability of a large number of Web services, finding an appropriate Web service according to the requirement of the user is a challenge. This warrants the need to establish an effective and reliable process of Web service discovery. A considerable body of research has emerged to develop methods to improve the accuracy of Web service discovery to match the best service. The process of Web service discovery results in suggesting many individual services that partially fulfil the user’s
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Bose, Aishwarya. "Effective web service discovery using a combination of a semantic model and a data mining technique." Queensland University of Technology, 2008. http://eprints.qut.edu.au/26425/.

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With the advent of Service Oriented Architecture, Web Services have gained tremendous popularity. Due to the availability of a large number of Web services, finding an appropriate Web service according to the requirement of the user is a challenge. This warrants the need to establish an effective and reliable process of Web service discovery. A considerable body of research has emerged to develop methods to improve the accuracy of Web service discovery to match the best service. The process of Web service discovery results in suggesting many individual services that partially fulfil the user’s
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Seifried, Eva [Verfasser], and Birgit [Akademischer Betreuer] Spinath. "Improving Learning and Teaching at Universities: The Potential of Applying Automatic Essay Scoring with Latent Semantic Analysis / Eva Seifried ; Betreuer: Birgit Spinath." Heidelberg : Universitätsbibliothek Heidelberg, 2016. http://d-nb.info/1180617347/34.

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Haridas, Mandar. "Exploring knowledge bases for engineering a user interests hierarchy for social network applications." Thesis, Manhattan, Kan. : Kansas State University, 2009. http://hdl.handle.net/2097/1528.

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Duff, Dawna Margaret. "Lexical semantic richness : effect on reading comprehension and on readers' hypotheses about the meanings of novel words." Diss., University of Iowa, 2015. https://ir.uiowa.edu/etd/1591.

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Purpose: This study investigates one possible reason for individual differences in vocabulary learning from written context. A Latent Semantic Analysis (LSA) model is used to motivate the prediction of a causal relationship between semantic knowledge for words in a text and the quality of their hypotheses about the semantics of novel words, an effect mediated by reading comprehension. The purpose of this study was to test this prediction behaviorally, using a within subject repeated measures design to control for other variables affecting semantic word learning. Methods: Participants in 6th gr
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Morel, Gwendolyn. "Educational Technology: A Comparison of Ten Academic Journals and the New Media Consortium Horizon Reports for the Period of 2000-2017." Thesis, University of North Texas, 2017. https://digital.library.unt.edu/ark:/67531/metadc1062887/.

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This exploratory and descriptive study provides an increased understanding of the topics being explored in both published research and industry reporting in the field of educational technology. Although literature in the field is plentiful, the task of synthesizing the information for practical use is a massive undertaking. Latent semantic analysis was used to review journal abstracts from ten highly respected journals and the New Media Consortium Horizon Reports to identify trends within the publications. As part of the analysis, 25 topics and technologies were identified in the combined corp
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King, John Douglas. "Deep Web Collection Selection." Thesis, Queensland University of Technology, 2004. https://eprints.qut.edu.au/15992/3/John_King_Thesis.pdf.

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The deep web contains a massive number of collections that are mostly invisible to search engines. These collections often contain high-quality, structured information that cannot be crawled using traditional methods. An important problem is selecting which of these collections to search. Automatic collection selection methods try to solve this problem by suggesting the best subset of deep web collections to search based on a query. A few methods for deep Web collection selection have proposed in Collection Retrieval Inference Network system and Glossary of Servers, Server system.
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King, John Douglas. "Deep Web Collection Selection." Queensland University of Technology, 2004. http://eprints.qut.edu.au/15992/.

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The deep web contains a massive number of collections that are mostly invisible to search engines. These collections often contain high-quality, structured information that cannot be crawled using traditional methods. An important problem is selecting which of these collections to search. Automatic collection selection methods try to solve this problem by suggesting the best subset of deep web collections to search based on a query. A few methods for deep Web collection selection have proposed in Collection Retrieval Inference Network system and Glossary of Servers Server system. The d
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Novák, Ján. "Automatická tvorba tezauru z wikipedie." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2011. http://www.nusl.cz/ntk/nusl-236964.

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This thesis deals with automatic acquiring thesauri from Wikipedia. It describes Wikipedia as a suitable data set for thesauri acquiring and also methods for computing semantic similarity of terms are described. The thesis also contains a description of concepts and implementation of the system for automatic thesauri acquiring. Finally, the implemented system is evaluated by the standard metrics, such as precision or recall.
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Papadouka, Maria Eirini. "Using Topic Models to Study Journalist-Audience Convergence and Divergence: The Case of Human Trafficking Coverage on British Online Newspapers." Thesis, University of North Texas, 2016. https://digital.library.unt.edu/ark:/67531/metadc862882/.

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Despite the accessibility of online news and availability of sophisticated methods for analyzing news content, no previous study has focused on the simultaneous examination of news coverage on human trafficking and audiences' interpretations of this coverage. In my research, I have examined both journalists' and commenters' topic choices in coverage and discussion of human trafficking from the online platforms of three British newspapers covering the period 2009–2015. I used latent semantic analysis (LSA) to identify emergent topics in my corpus of newspaper articles and readers' comments, and
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Alshareef, Abdulrhman M. "Academic Recommendation System Based on the Similarity Learning of the Citation Network Using Citation Impact." Thesis, Université d'Ottawa / University of Ottawa, 2019. http://hdl.handle.net/10393/39111.

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In today's significant and rapidly increasing amount of scientific publications, exploring recent studies in a given research area and building an effective scientific collaboration has become more challenging than any time before. Scientific production growth has been increasing the difficulties for identifying the most relevant papers to cite or to find an appropriate conference or journal to submit a paper to publish. As a result, authors and publishers rely on different analytical approaches in order to measure the relationship among the citation network. Different parameters have been use
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Macedo, Alessandra Alaniz. "Especificação, instanciação e experimentação de um arcabouço para criação automática de ligações hipertexto entre informações homogêneas." Universidade de São Paulo, 2004. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-05102004-113421/.

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Com a evolução da informática, diferentes meios de comunicação passaram a explorar a Web como um meio de divulgação de suas informações. Diferentes fontes de informações, diferentes estilos de escrita e a curiosidade nata do ser humano despertam o interesse de leitores por conhecer mais de um relato sobre um mesmo tema. Para que a leitura de diferentes relatos com conteúdo similar seja possível, leitores precisam procurar, ler e analisar informações fornecidas por diferentes fontes de informação. Essa atividade, além de exigir grande investimento de tempo, sobrecarrega cognitivamente usuários.
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Gorrell, Genevieve. "Generalized Hebbian Algorithm for Dimensionality Reduction in Natural Language Processing." Doctoral thesis, Linköping : Department of Computer and Information Science, Linköpings universitet, 2006. http://www.bibl.liu.se/liupubl/disp/disp2006/tek1045s.pdf.

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Zougris, Konstantinos. "Sociological Applications of Topic Extraction Techniques: Two Case Studies." Thesis, University of North Texas, 2015. https://digital.library.unt.edu/ark:/67531/metadc804982/.

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Limited research has been conducted with regards to the applicability of topic extraction techniques in Sociology. Addressing the modern methodological opportunities, and responding to the skepticism with regards to the absence of theoretical foundations supporting the use of text analytics, I argue that Latent Semantic Analysis (LSA), complemented by other text analysis techniques and multivariate techniques, can constitute a unique hybrid method that can facilitate the sociological interpretations of web-based textual data. To illustrate the applicability of the hybrid technique, I developed
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Pinheiro, José Claudio dos Santos. "USO DE TEORIAS NO CAMPO DE SISTEMAS DE INFORMAÇÃO: MAPEAMENTO USANDO TÉCNICAS DE MINERAÇÃO DE TEXTOS." Universidade Metodista de São Paulo, 2009. http://tede.metodista.br/jspui/handle/tede/152.

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Made available in DSpace on 2016-08-02T21:42:57Z (GMT). No. of bitstreams: 1 Jose Claudio dos Santos Pinheiro.pdf: 5349646 bytes, checksum: 057189cedae5b7fc79c3e7cec83d51aa (MD5) Previous issue date: 2009-09-17<br>This work aim to map the use of information system s theories, based on analytic resources that came from information retrieval techniques and data mining and text mining methodologies. The theories addressed by this research were Transactions Costs Economics (TCE), Resource-based view (RBV) and Institutional Theory (IT), which were chosen given their usefulness, while alternatives
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Ong, James Kwan Yau. "The predictability problem." Phd thesis, kostenfrei, 2007. http://opus.kobv.de/ubp/volltexte/2007/1502/.

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