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Dissertations / Theses on the topic 'Ontology and information retrieval'
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1
Tomassen, Stein L. "Conceptual Ontology Enrichment for Web Information Retrieval." Doctoral thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap, 2011. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-14270.
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Searching for information on the Web can be frustrating. One of the reasons is the ambiguity of words. The work presented in this thesis concentrates on how the effectiveness of standard information retrieval systems can be enhanced with semantic technologies like ontologies. Ontologies are knowledge models that can represent knowledge of any universe of discourse by describing how concepts of a domain are related. Creating and maintaining ontologies can be tedious and costly. However, we focus on reusing ontologies, rather than engineering, and on their applicability to improve the retrieval effectiveness of existing search systems. The aim of this work is to find an effective approach for applying ontologies to existing search systems. The basic idea is that these ontologies can be used to tackle the problem of ambiguous words and hence improve the retrieval effectiveness. Our approach to semantic search builds on feature vectors (FV). The basic idea is to connect the (standardised) domain terminology encoded in an ontology to the actual terminology used in a text corpus. Therefore, we propose to associate every ontology entity (classes and individuals are called entities in this work) with a FV that is tailored to the actual terminology used in a text corpus like the Web. These FVs are created off-line and later used on-line to filter (i.e. to disambiguate search) and re-rank the search results from an underlying search system. This pragmatic approach is applicable to existing search systems since it only depends on extending the query and presentation components, in other words there is no need to alter either the indexing or the ranking components of the existing systems. A set of experiments have been carried out and the results report on improvement by more than 10%. Furthermore, we have shown that the approach is neither dependent on highly specific queries nor on a collection comprised only of relevant documents. In addition, we have shown that the FVs are relatively persistent, i.e. little maintenance of the FVs is required. In this work, we focus on the creation and evaluation of these feature vectors. As a result, a part of the contribution of this work is a framework for the construction of FVs. Furthermore, we have proposed a set of metrics to measure the quality of the created FVs. We have also provided a set of guidelines for optimal construction of feature vectors for different categories of ontologies.
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Jimeno, Yepes Antonio José. "Ontology refinement for improved information retrieval in the biomedical domain." Doctoral thesis, Universitat Jaume I, 2009. http://hdl.handle.net/10803/384552.
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Este trabajo de tesis doctoral se centra en el uso de ontologías de dominio y su refinamiento enfocado a la recuperación de la información. El dominio seleccionado ha sido el de la Biomedicina, que dispone de una extensa colección de resúmenes en la base de datos Medline y recursos que facilitan la creación de ontologías muy extensas, tales como MeSH o UMLS.
En este trabajo se ha desarrollado también un modelo de formulación de consulta que permite relacionar un modelo de documento con una ontología dentro de los modelos de lenguaje. Además hemos desarrollado un algoritmo que permite mejorar la ontología para la tarea de recuperación de la información a partir de recursos no estructurados.
Los resultados muestran que el refinamiento de las ontologías aplicado a la recuperación de la información mejora el rendimiento, identificando automáticamente información no presente en la ontología. Además hemos comprobado que el tipo de contenido relevante para las consultas depende de propiedades relacionadas con el tipo de consulta y la colección de documentos. Los resultados están acordes con resultados existentes en el campo de la recuperación de la información.
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Mehalingam, Senthilkumar. "Ontology based code generation for datalogger." Diss., Online access via UMI:, 2006.
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Fischer, Wolf [Verfasser], and Bernhard [Akademischer Betreuer] Bauer. "Linguistically Motivated Ontology-Based Information Retrieval / Wolf Fischer. Betreuer: Bernhard Bauer." Augsburg : Universität Augsburg, 2013. http://d-nb.info/1077702795/34.
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Bhogal, Jagdev. "Investigating ontology based query expansion using a probabilistic retrieval model." Thesis, City University London, 2011. http://openaccess.city.ac.uk/2946/.
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This research briefly outlines the problems of traditional information retrieval systems and discusses the different approaches to inferring context in document retrieval. By context we mean word disambiguation which is achieved by exploring the generalisation-specialisation hierarchies within a given ontology. Specifically, we examine the use of ontology based query expansion for defining query context. Query expansion can be done in many ways and in this work we consider the use of relevance feedback and pseudo-relevance feedback for query expansion. We examine relevance feedback and pseudo-relevance to ascertain the existence of performance differences between relevance feedback and pseudo-relevance feedback. The information retrieval system used is based on the probabilistic retrieval model and the query expansion method is extended using information from a news domain ontology. The aim of this project is to assess the impact of the use of the ontology on the query expansion results. Our results show that ontology based query expansion has resulted in a higher number of relevant documents being retrieved compared to the standard relevance feedback process. Overall, ontology based query expansion improves recall but does not produce any significant improvements for the precision results. Pseudo-relevance feedback has achieved better results than relevance feedback. We also found that reducing or increasing the relevance feedback parameters (number of terms or number of documents) does not correlate with the results. When comparing the effect of varying the number of terms parameter with the number of documents parameter, the former benefits the pseudo-relevance feedback results but the latter has an additional effect on the relevance feedback results. There are many factors which influence the success of ontology based query expansion. The thesis discusses these factors and gives some guidelines on using ontologies for the purpose of query expansion.
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Chang, Jia Kang. "Investigation on applying modular ontology to statistical language model for information retrieval." Thesis, University of Central Lancashire, 2015. http://clok.uclan.ac.uk/11803/.
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The objective of this research is to provide a novel approach to improving retrieval performance by exploiting Ontology with the statistical language model (SLM). The proposed methods consist of two major processes, namely ontology-based query expansion (OQE) and ontology-based document classification (ODC). Research experiments have required development of an independent search tool that can combine the OQE and ODC in a traditional SLM-based information retrieval (IR) process using a Web document collection. This research considers the ongoing challenges of modular ontology enhanced SLM-based search and addresses three contribution aspects. The first concerns how to apply modular ontology to query expansion, in a bespoke language model search tool (LMST). The second considers how to incorporate OQE with the language model to improve the search performance. The third examines how to manipulate such semantic-based document classification to improve the smoothing accuracy. The role of ontology in the research is to provide formally described domains of interest that serve as context, to enhance system query effectiveness.
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Wang, Xinkai. "Chinese-English cross-lingual information retrieval in biomedicine using ontology-based query expansion." Thesis, University of Manchester, 2011. https://www.research.manchester.ac.uk/portal/en/theses/chineseenglish-crosslingual-information-retrieval-in-biomedicine-using-ontologybased-query-expansion(1b7443d3-3baf-402b-83bb-f45e78876404).html.
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In this thesis, we propose a new approach to Chinese-English Biomedical cross-lingual information retrieval (CLIR) using query expansion based on the eCMeSH Tree, a Chinese-English ontology extended from the Chinese Medical Subject Headings (CMeSH) Tree. The CMeSH Tree is not designed for information retrieval (IR), since it only includes heading terms and has no term weighting scheme for these terms. Therefore, we design an algorithm, which employs a rule-based parsing technique combined with the C-value term extraction algorithm and a filtering technique based on mutual information, to extract Chinese synonyms for the corresponding heading terms. We also develop a term-weighting mechanism. Following the hierarchical structure of CMeSH, we extend the CMeSH Tree to the eCMeSH Tree with synonymous terms and their weights. We propose an algorithm to implement CLIR using the eCMeSH Tree terms to expand queries. In order to evaluate the retrieval improvements obtained from our approach, the results of the query expansion based on the eCMeSH Tree are individually compared with the results of the experiments of query expansion using the CMeSH Tree terms, query expansion using pseudo-relevance feedback, and document translation. We also evaluate the combinations of these three approaches. This study also investigates the factors which affect the CLIR performance, including a stemming algorithm, retrieval models, and word segmentation.
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Chartrand, Tim. "Ontology-based extraction of RDF data from the World Wide Web /." Diss., CLICK HERE for online access, 2003. http://contentdm.lib.byu.edu/ETD/image/etd168.pdf.
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Modica, Giovanni. "A framework for automatic ontology generation from autonomous web applications." Master's thesis, Mississippi State : Mississippi State University, 2002. http://library.msstate.edu/etd/show.asp?etd=etd-09032002-165210.
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Ngo, Duy Hoa. "Enhancing Ontology Matching by Using Machine Learning, Graph Matching and Information Retrieval Techniques." Thesis, Montpellier 2, 2012. http://www.theses.fr/2012MON20096/document.
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Ces dernières années, les ontologies ont suscité de nombreux travaux dans le domaine du web sémantique. Elles sont utilisées pour fournir le vocabulaire sémantique permettant de rendre la connaissance du domaine disponible pour l'échange et l'interprétation au travers des systèmes d'information. Toutefois, en raison de la nature décentralisée du web sémantique, les ontologies sont très hétérogènes. Cette hétérogénéité provoque le problème de la variation de sens ou ambiguïté dans l'interprétation des entités et, par conséquent, elle empêche le partage des connaissances du domaine. L'alignement d'ontologies, qui a pour but la découverte des correspondances sémantiques entre des ontologies, devient une tâche cruciale pour résoudre ce problème d'hétérogénéité dans les applications du web sémantique. Les principaux défis dans le domaine de l'alignement d'ontologies ont été décrits dans des études récentes. Parmi eux, la sélection de mesures de similarité appropriées ainsi que le réglage de la configuration de leur combinaison sont connus pour être des problèmes fondamentaux que la communauté doit traiter. En outre, la vérification de la cohérence sémantique des correspondances est connue pour être une tâche importante. Par ailleurs, la difficulté du problème augmente avec la taille des ontologies. Pour faire face à ces défis, nous proposons dans cette thèse une nouvelle approche, qui combine différentes techniques issues des domaines de l'apprentissage automatique, d'appariement de graphes et de recherche d'information en vue d'améliorer la qualité de l'alignement d'ontologies. En effet, nous utilisons des techniques de recherche d'information pour concevoir de nouvelles mesures de similarité efficaces afin de comparer les étiquettes et les profils d'entités de contexte au niveau des entités. Nous appliquons également une méthode d'appariement de graphes appelée propagation de similarité au niveau de la structure qui découvre effectivement des correspondances en exploitant des informations structurelles des entités. Pour combiner les mesures de similarité au niveau des entités, nous transformons la tâche de l'alignement d'ontologie en une tâche de classification de l'apprentissage automatique. Par ailleurs, nous proposons une méthode dynamique de la somme pondérée pour combiner automatiquement les correspondances obtenues au niveau des entités et celles obtenues au niveau de la structure. Afin d'écarter les correspondances incohérentes, nous avons conçu une nouvelle méthode de filtrage sémantique. Enfin, pour traiter le problème de l'alignement d'ontologies à large échelle, nous proposons deux méthodes de sélection des candidats pour réduire l'espace de calcul.Toutes ces contributions ont été mises en œuvre dans un prototype nommé YAM++. Pour évaluer notre approche, nous avons utilisé des données du banc d'essai de la compétition OAEI : Benchmark, Conference, Multifarm, Anatomy, Library and Large Biomedical Ontologies. Les résultats expérimentaux montrent que les méthodes proposées sont très efficaces. De plus, en comparaison avec les autres participants à la compétition OAEI, YAM++ a montré sa compétitivité et a acquis une position de haut rangIn recent years, ontologies have attracted a lot of attention in the Computer Science community, especially in the Semantic Web field. They serve as explicit conceptual knowledge models and provide the semantic vocabularies that make domain knowledge available for exchange and interpretation among information systems. However, due to the decentralized nature of the semantic web, ontologies are highlyheterogeneous. This heterogeneity mainly causes the problem of variation in meaning or ambiguity in entity interpretation and, consequently, it prevents domain knowledge sharing. Therefore, ontology matching, which discovers correspondences between semantically related entities of ontologies, becomes a crucial task in semantic web applications.Several challenges to the field of ontology matching have been outlined in recent research. Among them, selection of the appropriate similarity measures as well as configuration tuning of their combination are known as fundamental issues that the community should deal with. In addition, verifying the semantic coherent of the discovered alignment is also known as a crucial task. Furthermore, the difficulty of the problem grows with the size of the ontologies. To deal with these challenges, in this thesis, we propose a novel matching approach, which combines different techniques coming from the fields of machine learning, graph matching and information retrieval in order to enhance the ontology matching quality. Indeed, we make use of information retrieval techniques to design new effective similarity measures for comparing labels and context profiles of entities at element level. We also apply a graph matching method named similarity propagation at structure level that effectively discovers mappings by exploring structural information of entities in the input ontologies. In terms of combination similarity measures at element level, we transform the ontology matching task into a classification task in machine learning. Besides, we propose a dynamic weighted sum method to automatically combine the matching results obtained from the element and structure level matchers. In order to remove inconsistent mappings, we design a new fast semantic filtering method. Finally, to deal with large scale ontology matching task, we propose two candidate selection methods to reduce computational space.All these contributions have been implemented in a prototype named YAM++. To evaluate our approach, we adopt various tracks namely Benchmark, Conference, Multifarm, Anatomy, Library and Large BiomedicalOntologies from the OAEI campaign. The experimental results show that the proposed matching methods work effectively. Moreover, in comparison to other participants in OAEI campaigns, YAM++ showed to be highly competitive and gained a high ranking position
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Muthaiyah, Saravanan. "A framework and methodology for ontology mediation through semantic and syntactic mapping." Fairfax, VA : George Mason University, 2008. http://hdl.handle.net/1920/3070.
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Thesis (Ph. D.)--George Mason University, 2008.Vita: p. 177. Thesis director: Larry Kerschberg. Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Information Technology. Title from PDF t.p. (viewed July 3, 2008). Includes bibliographical references (p. 169-176). Also issued in print.
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Deniz, Onur. "Ontology Based Text Mining In Turkish Radiology Reports." Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614145/index.pdf.
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Vast amount of radiology reports are produced in hospitals. Being in free text format and having errors due to rapid production, it continuously gets more complicated for radiologists and physicians to reach meaningful information. Though application of ontologies into bio-medical text mining has gained increasing interest in recent years, less work has been offered for ontology based retrieval tasks in Turkish language. In this work, an information extraction and retrieval system based on SNOMED-CT ontology has been proposed for Turkish radiology reports. Main purpose of this work is to utilize semantic relations in ontology to improve precision and recall rates of search results in domain. Practical problems encountered such as spelling errors, segmentation and tokenization of unstructured medical reports has also been addressed during the work.
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Morgenroth, Karlheinz. "Kontextbasiertes Information-Retrieval : Modell, Konzeption und Realisierung kontextbasierter Information-Retrieval-Systeme /." Berlin : Logos, 2006. http://deposit.ddb.de/cgi-bin/dokserv?id=2786087&prov=M&dok_var=1&dok_ext=htm.
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George, David. "Examining the application of modular and contextualised ontology in query expansions for information retrieval." Thesis, University of Central Lancashire, 2010. http://clok.uclan.ac.uk/1865/.
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This research considers the ongoing challenge of semantics-based search from the perspective of how to exploit Semantic Web languages for search in the current Web environment. The purpose of the PhD was to use ontology-based query expansion (OQE) to improve search effectiveness by increasing search precision, i.e. retrieving relevant documents in the topmost ranked positions in a returned document list. Query experiments have required a novel search tool that can combine Semantic Web technologies in an otherwise traditional IR process using a Web document collection.
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Yeung, Chung Kei. "Ontological model for information systems development methodology." HKBU Institutional Repository, 2006. http://repository.hkbu.edu.hk/etd_ra/702.
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Cui, Licong. "Ontology-guided Health Information Extraction, Organization, and Exploration." Case Western Reserve University School of Graduate Studies / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=case1401709795.
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Skovronski, John. "An ontology-based publish-subscribe framework." Diss., Online access via UMI:, 2006.
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Kubilay, Mustafa. "Special Index And Retrieval Mechanism For Ontology Based Medical Domain Search Engines." Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/2/12606470/index.pdf.
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This thesis focuses on index and retrieval mechanism of an ontology based medical domain search engine. First, indexing techniques and retrieval methods are reviewed. Then, a special indexing and retrieval mechanism are introduced. This thesis also specifies the functional requirements of these mechanisms. Finally, an evaluation is given by indicating the positive and negative aspects of mechanisms.
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Hermans, Jan. "Ontologiebasiertes Information-Retrieval für das Wissensmanagement." Berlin Logos-Verl, 2008. http://d-nb.info/992454247/04.
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Travillian, Ravensara S. "Ontology recapitulates phylogeny : design, implementation and potential for usage of a comparative anatomy information system /." Thesis, Connect to this title online; UW restricted, 2006. http://hdl.handle.net/1773/7156.
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Reul, Quentin H. "Role of description logic reasoning in ontology matching." Thesis, University of Aberdeen, 2012. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=186278.
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Semantic interoperability is essential on the Semantic Web to enable different information systems to exchange data. Ontology matching has been recognised as a means to achieve semantic interoperability on the Web by identifying similar information in heterogeneous ontologies. Existing ontology matching approaches have two major limitations. The first limitation relates to similarity metrics, which provide a pessimistic value when considering complex objects such as strings and conceptual entities. The second limitation relates to the role of description logic reasoning. In particular, most approaches disregard implicit information about entities as a source of background knowledge. In this thesis, we first present a new similarity function, called the degree of commonality coefficient, to compute the overlap between two sets based on the similarity between their elements. The results of our evaluations show that the degree of commonality performs better than traditional set similarity metrics in the ontology matching task. Secondly, we have developed the Knowledge Organisation System Implicit Mapping (KOSIMap) framework, which differs from existing approaches by using description logic reasoning (i) to extract implicit information as background knowledge for every entity, and (ii) to remove inappropriate correspondences from an alignment. The results of our evaluation show that the use of Description Logic in the ontology matching task can increase coverage. We identify people interested in ontology matching and reasoning techniques as the target audience of this work
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Ismail, Muhammad, and Attuallah Jan. "Context-based supply of documents in a healthcare process." Thesis, Tekniska Högskolan, Högskolan i Jönköping, JTH. Forskningsmiljö Informationsteknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-18513.
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The more enhanced and reliable healthcare facilities, depend partly on accumulated organizational knowledge. Ontology and semantic web are the key factors in long-term sustainability towards the improvement of patient treatment process. Generally, researchers have the common consensus that knowledge is hard to capture due to its implicit nature, making it hard to manage. Medical professionals spend more time on getting the right information at the right moment, which is already available on intranet/internet. Evaluating the literature is controversial but interesting debates on ontology and semantic web encouraged us to propose a method and 4-Tier Architecture for retrieving context-based document according to user’s information in healthcare organization. Medical professionals are facing problems to access relevant information and documents for performing different tasks in the patient-treatment process. We have focused to provide context-based retrieval of documents for medical professionals by developing a semantic web solution. We also developed different OWL ontology models, which are mainly used for semantic tagging in web pages and generating context to retrieve the relevant web page documents. In addition, we developed a prototype to testify our findings in health care sector with the goal of retrieving relevant documents in a practical manner.E-Health
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Duranti, Cleber Marchetti. "Seleção de notícias online para inteligência competitiva: uso de ontologia de domínio do negócio para expansão semântica da busca na internet." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/12/12139/tde-08112013-190539/.
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DURANTI, Cleber Marchetti. Seleção de notícias online para inteligência competitiva - Uso de ontologia de domínio do negócio para expansão semântica da busca na internet. São Paulo, 2013. Tese (Doutorado em Administração) - Departamento de Administração, Faculdade de Economia, Administração e Contabilidade da Universidade de São Paulo. A internet disponibiliza o acesso a notícias e informações em volume crescente a respeito do ambiente em que as empresas operam, e estas precisam se manter a par dos movimentos dos atores do seu mercado de atuação e dos temas pertinentes ao seu negócio para se manterem competitivas. O crescente volume de dados, porém, leva à sobrecarga de informações, quando o volume de informações disponíveis é maior que a capacidade de processamento dos usuários. Torna-se então necessário o desenvolvimento de métodos e ferramentas que ajudem a separar a informação potencialmente útil da informação irrelevante. Este trabalho apresenta o desenvolvimento de uma ferramenta que utiliza a modelagem da área de negócio na forma de uma ontologia como subsídio para formulação de melhores buscas na internet, através da expansão semântica interativa das palavras-chave utilizadas pelos usuários quando da busca num buscador comum da internet - ainda o método mais utilizado para coleta de informações da internet. Uma ontologia do domínio de negócio \"Outsourcing de TI\" e uma interface para uso dessa ontologia na expansão das buscas dentro deste domínio são desenvolvidos. O protótipo é testado por meio de simulações de buscas e testes por usuários da área de TI, com os quais é feito um levantamento de aceitação de tecnologia utilizando o modelo TAM-3 adaptado para a avaliação do protótipo. Os resultados do levantamento indicam uma boa aceitação da solução nos aspectos de utilidade, facilidade de uso e nas demais dimensões do modelo TAM3.The internet provides access to news and information in increasing volume about the environment in which companies operate, and they need to keep up to date about the movements of the actors of their market and the topics relevant to their business in order to keep their competitiveness. The growing volume of data, however, leads to information overload, when the amount of information available is larger than the processing capacity of its users. It becomes necessary then to develop methods and tools that help separate potentially useful information from irrelevant information. This research presents the development of a tool that uses the modeling of the a business area in the form of an ontology as a support for the formulation of better internet searches through interactive semantic expansion of keywords used by users when searching in an usual internet search engine - still the most widely used method for collecting information from the internet. An ontology of the business domain \"IT outsourcing\" and an interface to use this ontology in the expansion of searches in this area are developed. The prototype is tested by simulations and test searches by IT users with whom a survey is done using the qualitative model TAM-3 adapted to evaluate the prototype. The survey results show good acceptance of the solution in the aspects of usefulness, easy of use and the other dimensions of the TAM3 model.
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Kazadi, Yannick Kazela. "A framework for analysing the complexity of ontology." Thesis, Vaal University of Technology, 2016. http://hdl.handle.net/10352/456.
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M. Tech. (Department of Information and Communication Technology, Faculty of Applied and Computer Sciences), Vaal University of TechnologyThe emergence of the Semantic Web has resulted in more and more large-scale ontologies being developed in real-world applications to represent and integrate knowledge and data in various domains. This has given rise to the problem of selection of the appropriate ontology for reuse, among the set of ontologies describing a domain. To address such problem, it is argued that the evaluation of the complexity of ontologies of a domain can assist in determining the suitable ontologies for the purpose of reuse. This study investigates existing metrics for measuring the design complexity of ontologies and implements these metrics in a framework that provides a stepwise process for evaluating the complexity of ontologies of a knowledge domain. The implementation of the framework goes through a certain number of phases including the: (1) download of 100 Biomedical ontologies from the BioPortal repository to constitute the dataset, (2) the design of a set of algorithms to compute the complexity metrics of the ontologies in the dataset including the depth of inheritance (DIP), size of the vocabulary (SOV), entropy of ontology graphs (EOG), average part length (APL) and average number of paths per class (ANP), the tree impurity (TIP), relationship richness (RR) and class richness (CR), (3) ranking of the ontologies in the dataset through the aggregation of their complexity metrics using 5 Multi-attributes Decision Making (MADM) methods, namely, Weighted Sum Method (WSM), Weighted Product Method (WPM), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Weighted Linear Combination Ranking Technique (WLCRT) and Elimination and Choice Translating Reality (ELECTRE) and (4) validation of the framework through the summary of the results of the previous phases and analysis of their impact on the issues of selection and reuse of the biomedical ontologies in the dataset. The ranking results of the study constitute important guidelines for the selection and reuse of biomedical ontologies in the dataset. Although the proposed framework in this study has been applied in the biomedical domain, it could be applied in any other domain of Semantic Web to analyze the complexity of ontologies.
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Nagypál, Gábor. "Possibly imperfect ontologies for effective information retrieval." Karlsruhe : Univ.-Verl. Karlsruhe, 2007. http://d-nb.info/986790028/34.
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Sherman, Steven Jay. "A Process-Oriented Ontology for Representing Software Engineering Project Knowledge." NSUWorks, 2009. http://nsuworks.nova.edu/gscis_etd/302.
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Organizational project knowledge is not being captured, consolidated, and organized, making it difficult to learn from past projects, expose the knowledge of the most experienced people, or share experience across geographic project locations. The lack of an ontology for representing this comprehensive project store inhibits its creation and the development of tools to operate on it.
Process-orientation links organizational resources or artifacts with process phases and workflow. A process-orientation in knowledge management can be used to add contextual metadata to knowledge artifacts. Context can be used to improve information retrieval precision.
Therefore, the study proposed a process-oriented ontology to improve the transfer of software engineering project knowledge.
Four questions guided the research:
What knowledge about projects should be captured? Are all project artifacts necessary and are they all equally valuable?
How can process-orientation be applied to a software engineering project knowledge ontology?
Are current knowledge representation languages appropriate for the task?
Can software development project knowledge, as represented by this ontology, be captured and retrieved effectively in a KMS?
Literature research and an empirical laboratory study answered all of the questions:
Four areas of project knowledge are particularly valuable in terms of their impact on project success; requirements, revisions, risks, and resolutions. These areas also cover a meaningful breadth of software engineering project knowledge.
A process abstraction was created that breaks a project down into eleven phases. These phases were the basis for a class definition that was added as a peer class to the knowledge artifacts.
Using Protégé, the Process-Oriented Ontology for Software Engineering (POSE) was successfully implemented in OWL-DL.
Project knowledge from a software organization was used to construct two knowledgebases: one using Google Desktop and the other using Protégé and POSE. Results demonstrated that software engineering project knowledge, as represented by POSE, can be effectively captured and retrieved.
POSE-enhanced search was superior to keyword search. Google was comparable in broad text search. But the benefits of metadata and semantics proved to have significant advantages for ontologies. Process-orientation was also validated as a contributor to improved classification and retrieval.
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Alazemi, Awatef M. "A new methodology for designing a multi-lingual bio-ontology : an application to Arabic-English bio-information retrieval." Thesis, University of Salford, 2010. http://usir.salford.ac.uk/26507/.
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Ontologies are becoming increasingly important in the biomedical domain since they enable knowledge sharing in a formal, homogeneous and unambiguous way. Furthermore, biological discoveries are being reported at an extremely rapid rate. This new information is found in diverse resources that encompass a broad array of journal articles and public databases associated with different sub-disciplines within biology and medicine in different languages. However, finding relevant multilingual biological dedicated ontology to the digestive system ontology among a large collection of information is recognized as a critical knowledge gap in science. Consequently, this research argues the real need to highlight the area of ontology in a sense of searching in bio-lingual, representing concepts and inter-concept relationships. English-Arabic human digestive system ontology (DISUS) and its methodology were created to demonstrate the above notion. The approach adopted for this research involved creating a new integrated reengineered methodology for a novel first attempt multilingual (English-Arabic) bio-ontology for the purpose of information retrieval and knowledge discovery. The targeted DISUS ontology is to represent digestive system knowledge and to ease knowledge sharing among the end users in the biology and medicine context .The integrated generic methodology is constitutes of four phases the planning phase which shed light on the scope and purpose of the domain and the functioning of knowledge acquisition, the conceptualisation phase organizes unstructured knowledge to structured. The ontology construction which involves the integration and merging among the core and sub-ontologies. The evaluation phase which finalizes the whole work and this is executed by domain experts. Evaluation of multilingual DISUS carried out through qualitative and quantitative approaches with biological and medical experts, validation was utilized through information retrieval technique and has revealed the effectiveness and robustness of using DISUS ontology as a way for concept mapping between Arabic-English ontologies terms for bilingual searches.
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Zhou, Yuanqiu. "Generating Data-Extraction Ontologies By Example." Diss., CLICK HERE for online access, 2005. http://contentdm.lib.byu.edu/ETD/image/etd1115.pdf.
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Vickers, Mark S. "Ontology-Based Free-Form Query Processing for the Semantic Web." Diss., CLICK HERE for online access, 2006. http://contentdm.lib.byu.edu/ETD/image/etd1353.pdf.
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Zhan, Pei. "An ontology-based approach for semantic level information exchange and integration in applications for product lifecycle management." Online access for everyone, 2007. http://www.dissertations.wsu.edu/Dissertations/Summer2007/P_Zhan_080607.pdf.
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Cimiano, Philipp. "Ontology learning and population from text : algorithms, evaluation and applications /." New York, NY : Springer, 2006. http://www.loc.gov/catdir/enhancements/fy0824/2006931701-d.html.
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Hinderer, Eugene Waverly III. "COMPUTATIONAL TOOLS FOR THE DYNAMIC CATEGORIZATION AND AUGMENTED UTILIZATION OF THE GENE ONTOLOGY." UKnowledge, 2019. https://uknowledge.uky.edu/biochem_etds/43.
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Ontologies provide an organization of language, in the form of a network or graph, which is amenable to computational analysis while remaining human-readable. Although they are used in a variety of disciplines, ontologies in the biomedical field, such as Gene Ontology, are of interest for their role in organizing terminology used to describe—among other concepts—the functions, locations, and processes of genes and gene-products. Due to the consistency and level of automation that ontologies provide for such annotations, methods for finding enriched biological terminology from a set of differentially identified genes in a tissue or cell sample have been developed to aid in the elucidation of disease pathology and unknown biochemical pathways. However, despite their immense utility, biomedical ontologies have significant limitations and caveats. One major issue is that gene annotation enrichment analyses often result in many redundant, individually enriched ontological terms that are highly specific and weakly justified by statistical significance. These large sets of weakly enriched terms are difficult to interpret without manually sorting into appropriate functional or descriptive categories. Also, relationships that organize the terminology within these ontologies do not contain descriptions of semantic scoping or scaling among terms. Therefore, there exists some ambiguity, which complicates the automation of categorizing terms to improve interpretability.
We emphasize that existing methods enable the danger of producing incorrect mappings to categories as a result of these ambiguities, unless simplified and incomplete versions of these ontologies are used which omit problematic relations. Such ambiguities could have a significant impact on term categorization, as we have calculated upper boundary estimates of potential false categorizations as high as 121,579 for the misinterpretation of a single scoping relation, has_part, which accounts for approximately 18% of the total possible mappings between terms in the Gene Ontology. However, the omission of problematic relationships results in a significant loss of retrievable information. In the Gene Ontology, this accounts for a 6% reduction for the omission of a single relation. However, this percentage should increase drastically when considering all relations in an ontology. To address these issues, we have developed methods which categorize individual ontology terms into broad, biologically-related concepts to improve the interpretability and statistical significance of gene-annotation enrichment studies, meanwhile addressing the lack of semantic scoping and scaling descriptions among ontological relationships so that annotation enrichment analyses can be performed across a more complete representation of the ontological graph.
We show that, when compared to similar term categorization methods, our method produces categorizations that match hand-curated ones with similar or better accuracy, while not requiring the user to compile lists of individual ontology term IDs. Furthermore, our handling of problematic relations produces a more complete representation of ontological information from a scoping perspective, and we demonstrate instances where medically-relevant terms--and by extension putative gene targets--are identified in our annotation enrichment results that would be otherwise missed when using traditional methods. Additionally, we observed a marginal, yet consistent improvement of statistical power in enrichment results when our methods were used, compared to traditional enrichment analyses that utilize ontological ancestors. Finally, using scalable and reproducible data workflow pipelines, we have applied our methods to several genomic, transcriptomic, and proteomic collaborative projects.
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Fernandes, Joliza Chagas. "O universo e as relações de significação da web: semiose nas ontologias." Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/27/27151/tde-16042013-150137/.
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As dificuldades de acesso à informação na Web são decorrentes, dentre outras, da ausência ou inadequação do tratamento das informações. Entre as diversas propostas de filtragem de conteúdos de informação disponíveis na Web tem tido destaque a ferramenta denominada Ontologia. As potencialidades das Ontologias para lidar com problemas semânticos, sobretudo quando há grandes volumes de informação, parece promissor. Dessa forma, a reflexão teórica e a observação empírica sobre as Ontologias são importantes e necessárias para compreender seus aspectos semânticos e formais (lógicos). Assim, com base na teoria peirceana, mais especificamente a teoria do interpretante, o estudo focalizou as questões que envolvem as relações semânticas e formais das Ontologias com o fim de identificar traços que permitam sistematizar parâmetros teóricos e metodológicos de sua construção e avaliação. Para tanto, adotou-se como estudo de caso a ontologia Radlex, instrumento ontógico da área da Saúde disponível gratuitamente na Web. Para a análise foram considerados 615 termos selecionados a partir de quatro classes das principais categorias do Radlex, a saber: \"class Image Observation Characterístic\", \"class Pathophysiologic Process Modifier\", \"class Anatomical Cluster\" e \"class Object\". De acordo com as observações, concluiu-se que não basta a existência de aplicativos automatizados relevantes para o bom funcionamento desses instrumentos; são necessárias ações direcionadas para as questões de produção de sentido, que reflitam as necessidades informacionais dos pesquisadores que os utilizam. No caso do Radlex, apesar de trazer em sua estrutura conceitual todos os elementos necessários e pertinentes a uma representação da informação, é necessário enriquecê-la com relações semânticas e formais adicionais sobre a Radiologia.The difficulties to access information on the web are due, among other things, to the absence or inadequacy of the techiniques used in their organization Among the various proposals for content filtering available on the Web ther is a prominent tool called Ontology. The potential of ontologies to deal with semantic problems, especially when there are large volumes of information, looks promising. On the other hand, theoretical and empirical observation on Ontologies are important and necessary to deeply understand aspects of semantic and formal (logical) relationships between terms they contain. Thus, based on Peirce\'s theory, more specifically the Theory of the interpretant, the study focused on issues involving the formal and semantic relationships of ontologies, itending to identify aspects to draw up parameters for its construction and evaluation. To this endd, it was adopted as a case study the Radlex Ontology, complex health area ontological instrument available for free on the Web. For analysis 615 terms were selected from four classes of Radlex main categories, namely: \"class Image Characteristic Observation\", \"class Modifier Pathophysiologic Process\", \"class Anatomical Cluster\" and \"class Object\". According to the observations, we concluded that the existence of automated applications is not sufficient; it is necessary actions directed to the issues of meaning production, reflecting the information needs of researchers who use the ontologies. In the case of Radlex, despite bringing the necessary conceptual structure to represent information, the majority are hierarchical. Sinonimy relationships are absent. It is necessary to enrich it with dditional formal and semantic relationships non Radiology.
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Gängler, Thomas. "Semantic Federation of Musical and Music-Related Information for Establishing a Personal Music Knowledge Base." Master's thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2011. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-72434.
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Music is perceived and described very subjectively by every individual. Nowadays, people often get lost in their steadily growing, multi-placed, digital music collection. Existing music player and management applications get in trouble when dealing with poor metadata that is predominant in personal music collections. There are several music information services available that assist users by providing tools for precisely organising their music collection, or for presenting them new insights into their own music library and listening habits. However, it is still not the case that music consumers can seamlessly interact with all these auxiliary services directly from the place where they access their music individually. To profit from the manifold music and music-related knowledge that is or can be available via various information services, this information has to be gathered up, semantically federated, and integrated into a uniform knowledge base that can personalised represent this data in an appropriate visualisation to the users. This personalised semantic aggregation of music metadata from several sources is the gist of this thesis. The outlined solution particularly concentrates on users’ needs regarding music collection management which can strongly alternate between single human beings. The author’s proposal, the personal music knowledge base (PMKB), consists of a client-server architecture with uniform communication endpoints and an ontological knowledge representation model format that is able to represent the versatile information of its use cases. The PMKB concept is appropriate to cover the complete information flow life cycle, including the processes of user account initialisation, information service choice, individual information extraction, and proactive update notification. The PMKB implementation makes use of SemanticWeb technologies. Particularly the knowledge representation part of the PMKB vision is explained in this work. Several new Semantic Web ontologies are defined or existing ones are massively modified to meet the requirements of a personalised semantic federation of music and music-related data for managing personal music collections. The outcome is, amongst others, • a new vocabulary for describing the play back domain, • another one for representing information service categorisations and quality ratings, and • one that unites the beneficial parts of the existing advanced user modelling ontologies. The introduced vocabularies can be perfectly utilised in conjunction with the existing Music Ontology framework. Some RDFizers that also make use of the outlined ontologies in their mapping definitions, illustrate the fitness in practise of these specifications. A social evaluation method is applied to carry out an examination dealing with the reutilisation, application and feedback of the vocabularies that are explained in this work. This analysis shows that it is a good practise to properly publish Semantic Web ontologies with the help of some Linked Data principles and further basic SEO techniques to easily reach the searching audience, to avoid duplicates of such KR specifications, and, last but not least, to directly establish a \"shared understanding\". Due to their project-independence, the proposed vocabularies can be deployed in every knowledge representation model that needs their knowledge representation capacities. This thesis added its value to make the vision of a personal music knowledge base come true.
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Demirsoy, Ali. "Using Semantic Knowledge Management Systems To Overcome Information Overload Problems In Software Engineering." Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-5727.
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Context. Information overload is an increasingly important problem of our age where the amount of data we have is expanding drastically with the use of digital communication. Information retrieval models are developed to help overcoming this problem with computerized tools. Semantic information retrieval, which means retrieving information based on the interpretations of meanings of the words, is one of these models and started to be used commonly to handle large amount of data in the Internet and in enterprises to overcome information overload problems. Objectives. In this study we investigate different information retrieval models for using with knowledge management systems in large-scale organizations from the perspective of software engineers. To this end, we aim at identifying existing issues and needs about information overload and then assessing different solutions against these needs. Afterwards, we analyze the chosen solution, which is semantic search, and define and carry out an implementation process to reflect on it. Finally, the usefulness and feasibility of this type of solutions to overcome the specified information overload problems in software engineering is studied and discussed. Methods. We performed a literature review to extract the existing knowledge, technology, and the problems and solutions in the defined context. Then a case study was conducted at a development site of Ericsson AB in Sweden. Case study involved unstructured and semi-structured interviews for data collection, and an implementation attempt for a simple semantic knowledge management system. Thematic Coding Analysis method is used for qualitative data analysis. Results. We identified 23 codes that are categorized under 8 themes from the opinions of company practitioners about semantic knowledge management systems. They are mainly about the existing problems, arguments for using semantic system for solving them, and suggestions and challenges. Conclusions. We conclude that semantic knowledge management systems have a very high potential to solve information overload problems in software engineering if the necessary measures are taken. We found that the problems are related to search engine and the document structure of the tools; usefulness of semantic system is the capability of ontology based retrieval to filter out irrelevant documents and extract hidden data and people’s skills and interests; and finally the challenge is the necessary endeavor to elicit and satisfy all the needs.
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Caubet, Marc, and Mònica Cifuentes. "Extracting metadata from textual documents and utilizing metadata for adding textual documents to an ontology." Thesis, Växjö universitet, Matematiska och systemtekniska institutionen, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:vxu:diva-534.
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The term Ontology is borrowed from philosophy, where an ontology is a systematic account of Existence. In Computer Science, ontology is a tool allowing the effective use of information, making it understandable and accessible to the computer. For these reasons, the study of ontologies gained growing interest recently. Our motivation is to create a tool able to build ontologies from a set of textual documents. We present a prototype implementation which extracts metadata from textual documents and uses the metadata for adding textual documents to an ontology. In this paper we will investigate which techniques we have available and which ones have been used to accomplish our problem. Finally, we will show a program written in Java which allows us to build ontologies from textual documents using our approach.
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Wang, Wei. "Automated spatiotemporal and semantic information extraction for hazards." Diss., University of Iowa, 2014. https://ir.uiowa.edu/etd/1415.
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This dissertation explores three research topics related to automated spatiotemporal and semantic information extraction about hazard events from Web news reports and other social media. The dissertation makes a unique contribution of bridging geographic information science, geographic information retrieval, and natural language processing. Geographic information retrieval and natural language processing techniques are applied to extract spatiotemporal and semantic information automatically from Web documents, to retrieve information about patterns of hazard events that are not explicitly described in the texts. Chapters 2, 3 and 4 can be regarded as three standalone journal papers. The research topics covered by the three chapters are related to each other, and are presented in a sequential way. Chapter 2 begins with an investigation of methods for automatically extracting spatial and temporal information about hazards from Web news reports. A set of rules is developed to combine the spatial and temporal information contained in the reports based on how this information is presented in text in order to capture the dynamics of hazard events (e.g., changes in event locations, new events occurring) as they occur over space and time. Chapter 3 presents an approach for retrieving semantic information about hazard events using ontologies and semantic gazetteers. With this work, information on the different kinds of events (e.g., impact, response, or recovery events) can be extracted as well as information about hazard events at different levels of detail. Using the methods presented in Chapter 2 and 3, an approach for automatically extracting spatial, temporal, and semantic information from tweets is discussed in Chapter 4. Four different elements of tweets are used for assigning appropriate spatial and temporal information to hazard events in tweets. Since tweets represent shorter, but more current information about hazards and how they are impacting a local area, key information about hazards can be retrieved through extracted spatiotemporal and semantic information from tweets.
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Sánchez, David. "Domain ontology learning from the web an unsupervised, automatic and domain independent approach." Saarbrücken VDM Verlag Dr. Müller, 2007. http://d-nb.info/991459016/04.
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Zitzelberger, Andrew J. "HyKSS: Hybrid Keyword and Semantic Search." BYU ScholarsArchive, 2011. https://scholarsarchive.byu.edu/etd/2832.
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The rapid production of digital information makes the task of locating relevant information increasingly difficult. Keyword search alleviates this difficulty by retrieving documents containing keywords of interest. However, keyword search suffers from a number of issues such ambiguity, synonymy, and the inability to handle semantic constraints. Semantic search helps resolve these issues but is limited by the quality of annotations which are likely to be incomplete or imprecise. Hybrid search, a search technique that combines the merits of both keyword and semantic search, appears to be a promising solution. In this work we introduce HyKSS, a hybrid search system driven by extraction ontologies for both annotation creation and query interpretation. HyKSS is not limited to a single domain, but rather allows queries to cross ontological boundaries. We show that our hybrid search system, which uses a query driven dynamic ranking mechanism, outperforms keyword and semantic search in isolation, as well as a number of other non-HyKSS hybrid ranking approaches, over data sets of short topical documents. We also find that there is not a statistically significant difference between using multiple ontologies for query generation and simply selecting and using the best matching ontology.
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Hamilton, John, Ronald Fernandes, Timothy Darr, Michael Graul, Charles Jones, and Annette Weisenseel. "A Model-Based Methodology for Managing T&E Metadata." International Foundation for Telemetering, 2009. http://hdl.handle.net/10150/606019.
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ITC/USA 2009 Conference Proceedings / The Forty-Fifth Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2009 / Riviera Hotel & Convention Center, Las Vegas, NevadaIn this paper, we present a methodology for managing diverse sources of T&E metadata. Central to this methodology is the development of a T&E Metadata Reference Model, which serves as the standard model for T&E metadata types, their proper names, and their relationships to each other. We describe how this reference model can be mapped to a range's own T&E data and process models to provide a standardized view into each organization's custom metadata sources and procedures. Finally, we present an architecture that uses these models and mappings to support cross-system metadata management tasks and makes these capabilities accessible across the network through a single portal interface.
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Ducrou, Amanda Joanne. "Complete interoperability in healthcare technical, semantic and process interoperability through ontology mapping and distributed enterprise integration techniques /." Access electronically, 2009. http://ro.uow.edu.au/theses/3048.
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Chétrit, Héloèise. "Ett verktyg för konstruktion av ontologier från text." Thesis, Linköping University, Department of Computer and Information Science, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2228.
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With the growth of information stored over Internet, especially in the biological field, and with discoveries being made daily in this domain, scientists are faced with an overwhelming amount of articles. Reading all published articles is a tedious and time-consuming process. Therefore a way to summarise the information in the articles is needed. A solution is the derivation of an ontology representing the knowledge enclosed in the set of articles and allowing to browse through them.
In this thesis we present the tool Ontolo, which allows to build an initial ontology of a domain by inserting a set of articles related to that domain in the system. The quality of the ontology construction has been tested by comparing our ontology results for keywords to the ones provided by the Gene Ontology for the same keywords.
The obtained results are quite promising for a first prototype of the system as it finds many common terms on both ontologies for justa few hundred of inserted articles.
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Feliu, Judit. "Relacions conceptuals i terminologia: anàlisi i proposta de detecció semiautomàtica." Doctoral thesis, Universitat Pompeu Fabra, 2004. http://hdl.handle.net/10803/7494.
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Aquesta tesi doctoral té com a objectiu principal establir les bases per a un sistema de detecció semiautomàtica de relacions conceptuals a partir de textos especialitzats. Per arribar a aquest objectiu, la tesi presenta una definició de relació conceptual en el marc d'un enfocament comunicatiu de la terminologia i, a partir d'aquesta definició, l'autora detecta i aplica diversos marcadors lingüístics verbals per aïllar fragments textuals que continguin unitats de coneixement especialitzat, vehiculades mitjançant termes i relacions conceptuals. D'aquesta manera es pretén recuperar fragments de coneixement especialitzat a partir dels nusos de coneixement i de les seves relacions en textos de l'àmbit del genoma humà.Una de les aportacions principals d'aquesta tesi és l'aplicació d'una tipologia de relacions conceptuals validada empíricament a partir de textos especialitzats a la creació i alimentació d'una ontologia sobre el genoma humà. I orientat a complir l'objectiu general d'aquest treball, la detecció semiautomàtica de relacions conceptuals, l'autora proposa estratègies sintàctiques i semàntiques que permetin refinar al màxim aquests elements clau en l'organització de la informació especialitzada, combinant aquestes estratègies amb un detector i un extractor de terminologia.
The main goal of this Ph. dissertation is to establish the ground basis for a semiautomatic conceptual relations detector on the basis of specialised texts. In order to attain this goal, the Ph. dissertation includes a new definition of conceptual relations in a communicative approach to terminology. From this definition, the author detects and applies different linguistic verbal markers to isolate textual fragments containing specialised knowledge units expressed by terms and conceptual relations. The aim is to retrieve specialised knowledge fragments from knowledge nodes and the relations they establish among them in the human genome domain.
One of the main contributions of this work is the application of a typology of conceptual relations empirically validated on the basis of specialised texts on the construction and updating of an ontology about the human genome domain. As for the general goal, the semiautomatic detection of conceptual relations, the author proposes syntactic and semantic strategies for the maximum refinement of the detection of these key elements in the specialised information organisation, together with the use of a term detector and extractor.
Podeu consultar material addicional a http://repositori.upf.edu/handle/10230/6323
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Botero, Sergio William. "Extração de relações semanticas via análise de correlação de termos em documentos." [s.n.], 2008. http://repositorio.unicamp.br/jspui/handle/REPOSIP/259205.
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Orientador: Ivan Luiz Marques RicarteDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação
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Resumo: Sistemas de recuperação de informação são ferramentas para automatizar os procedimentos de busca por informações. Surgiram com propostas simples nas quais a recuperação era baseada exclusivamente na sintaxe das palavras e evoluíram para sistemas baseados na semântica das palavras como, por exemplo, os que utilizam ontologias. Entretanto, a especificação manual de ontologias é uma tarefa extremamente custosa e sujeita a erros humanos. Métodos automáticos para a construção de ontologias mostraram-se ineficientes, identificando falsas relações semânticas. O presente trabalho apresenta uma técnica baseada em processamento de linguagem natural e um novo algoritmo de agrupamento para a extração semi-automática de relações que utiliza o conteúdo dos documentos, uma ontologia de senso comum e supervisão do usuário para identificar corretamente as relações semânticas. A proposta envolve um estágio que utiliza recursos lingüísticos para a extração de termos e outro que utiliza algoritmos de agrupamento para a identificação de conceitos e relações semânticas de instanciação entre termos e conceitos. O algoritmo proposto é baseado em técnicas de agrupamento possibilístico e de bi-agrupamento e permite a extração interativa de conceitos e relações. Os resultados são promissores, similares às metodologias mais recentes, com a vantagem de permitir a supervisão do processo de extração
Abstract: Information Retrieval systems are tools to automate the searching for information. The first implementations were very simple, based exclusively on word syntax, and have evolved to systems that use semantic knowledge such as those using ontologies. However, the manual specification is an expensive task and subject to human mistakes. In order to deal with this problem, methodologies that automatically construct ontologies have been proposed but they did not reach good results, identifying false semantic relation between words. This work presents a natural language processing technique e a new clustering algorithm for the semi-automatic extraction of semantic relations by using the content of the document, a commom-sense ontology, and the supervision of the user to correctly identify semantic relations. The proposal encompasses a stage that uses linguistic resources to extract the terms and another stage that uses clustering algorithms to identify concepts and instanceof relations between terms and concepts. The proposed algorithm is based on possibilistic clustering and bi-clustering techniques and it allows the interative extraction of concepts. The results are promising, similar to the most recent methodologies, with the advantage of allowing the supervision of the extraction process
Mestrado
Engenharia de Computação
Mestre em Engenharia Elétrica
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Figueiras, Paulo Alves. "A framework for supporting knowledge representation – an ontological based approach." Master's thesis, Faculdade de Ciências e Tecnologia, 2012. http://hdl.handle.net/10362/7576.
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Dissertação para obtenção do Grau de Mestre em
Engenharia Electrotécnica e de ComputadoresThe World Wide Web has had a tremendous impact on society and business in just a few years by making information instantly available. During this transition from physical to electronic means for information transport, the content and encoding of information has remained natural language and is only identified by its URL. Today, this is perhaps the most significant obstacle to streamlining business processes via the web. In order that processes may execute without human intervention, knowledge sources, such as documents, must become more machine understandable and must contain other information besides their main contents and URLs. The Semantic Web is a vision of a future web of machine-understandable data. On a machine understandable web, it will be possible for programs to easily determine what knowledge sources are about. This work introduces a conceptual framework and its implementation to support the classification and discovery of knowledge sources, supported by the above vision, where such sources’ information is structured and represented through a mathematical vector that semantically pinpoints the relevance of those knowledge sources within the domain of interest of each user. The presented work also addresses the enrichment of such knowledge representations, using the statistical relevance of keywords based on the classical vector space model concept, and extending it with ontological support, by using concepts and semantic relations, contained in a domain-specific ontology, to enrich knowledge sources’ semantic vectors. Semantic vectors are compared against each other, in order to obtain the similarity between them, and better support end users with knowledge source retrieval capabilities.
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Shankar, Arunprasath. "ONTOLOGY-DRIVEN SEMI-SUPERVISED MODEL FOR CONCEPTUAL ANALYSIS OF DESIGN SPECIFICATIONS." Case Western Reserve University School of Graduate Studies / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=case1401706747.
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Santos, Edson Tafeli Carneiro dos. "Gestão eletrônica de documentos: gerenciamento do conhecimento para grupos de pesquisa." Universidade Presbiteriana Mackenzie, 2007. http://tede.mackenzie.br/jspui/handle/tede/1449.
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Previous issue date: 2007-03-12Instituto Presbiteriano Mackenzie
The evolution of information and data base management systems, artificial intelligence and neural networks, among other technologies, had contributed to the manipulation of an enormous amount of data and information by computational systems, what resulted in an increase of the information generated after the last half of XX century. The new configuration of the global world and the emerged information age had propitiated a vast amount of available information not ever seen at other times. Thus, information that needs to be accessed can be recovered more efficiently with the help of a specialized computational tool in document management. Also, in a research group, the data manipulated and the scientific and technical information generated by members of this group, promote a mass of information and knowledge that deserves to be managed. This work contemplates the management of documents and information of a determined research group, by means of the adaptation of concepts and pertinent areas taxonomy to the functionalities of an existing electronic document management tool, so that this information can be managed.
A evolução dos sistemas de informação, dos sistemas gerenciadores de banco de dados, da inteligência artificial e das redes neurais, dentre outras tecnologias, contribuíram para que os sistemas computacionais pudessem manipular uma enorme quantidade de dados, e por conseqüência, a geração de informação aumentou após a última metade do século XX. A nova configuração do mundo globalizado e o surgimento da era da informação propiciaram, de uma forma singular e não vivenciada em outras épocas, uma vasta quantidade de informações. Assim, uma informação que necessite ser acessada, pode ser obtida de forma mais eficiente com o auxílio de ferramentas computacionais especializadas em gestão de documentos. Também, em um grupo de pesquisas, os dados que são trabalhados e as informações técnicas geradas, promovem uma massa de informações e conhecimentos que merece ser gerenciada. Dessa forma, neste trabalho, pretende-se adaptar às funcionalidades existentes de uma ferramenta de gerenciamento eletrônico de documentos, por meio de uma taxonomia de conceitos e áreas pertinentes, os documentos e o conhecimento de determinado grupo de pesquisa, para que possam ser gerenciados.
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Wilmering, Thomas. "Applications of Semantic Web technologies in music production." Thesis, Queen Mary, University of London, 2014. http://qmro.qmul.ac.uk/xmlui/handle/123456789/9078.
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The development of tools and services for the realisation of the Semantic Web has been a very active field of research in recent years, with a strong focus on linking existing data. In the field of music information management, Semantic Web technologies may facilitate searching and browsing, and help to reveal relationships with data from other domains. At the same time, many algorithms have been developed to extract low and high-level features, which enable the user to analyse music and audio in detail. The use of semantics in the process of music production however is still a relatively new field of research. With computer systems and music processing applications becoming increasingly powerful and complex in their underlying structure, semantics can help musicians and producers in decision processes, and provide more natural interactions with the systems. Audio effects represent an integral part in modern music production. They modify an input signal and may be applied in order to enhance the perceived quality of a sound or to make more artistic changes to it in the composition process. Employing music information retrieval (MIR) and Semantic Web technologies specifically for the control of audio effects has the potential to be a significant step in their evolution. Detailed descriptions of the use of audio effects in a music production project can additionally facilitate the description of work flows and the reproducibility of production procedures, adding an additional layer of depth to MIR. We substantiate the hypothesis that the collection of audio related metadata during the production process is beneficial, by comparing the results of various feature extraction techniques on audio material before and after the application of audio effects. We develop a formal Semantic Web ontology for the domain of Audio Effects in the context of music production. The ontology enables the creation of detailed metadata about audio effects implementations within the Studio Ontology framework for use in music production projects. The ontology contains inter-linkable classification systems based on different criteria constituting an interdisciplinary classification. Finally, we evaluate the ontology and present several use cases and applications, such as adaptive audio effects using and creating semantic metadata.
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Lopes, Tatiane dos Santos de Freitas [UNESP]. "Ontologia como interface de apresentação de resultados de busca: uma proposta baseada no modelo espaço vetorial." Universidade Estadual Paulista (UNESP), 2017. http://hdl.handle.net/11449/151715.
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Um sistema de recuperação de informação é um elemento mediador entre um acervo documental e os usuários que buscam por documentos relevantes. Nesse contexto, as interfaces desempenham uma função importante: em um primeiro momento, auxiliando o usuário na tarefa de expressar a sua necessidade de informação por meio de uma expressão de busca e, em um segundo momento, fornecendo recursos para ajudá-lo a selecionar documentos relevantes dentre os resultados obtidos. A recuperação de informação é um processo linguístico cuja eficiência depende de coincidências terminológicas entre a expressão de busca do usuário e a representação dos documentos. Este trabalho propõe um modelo de interface na qual a estrutura terminológica de uma ontologia é utilizada para auxiliar o usuário na seleção de documentos relevantes dentre aqueles resultantes de sua busca. Caracteriza-se como uma pesquisa de natureza aplicada, e exploratória e bibliográfica quanto aos procedimentos. Conclui-se que a apresentação visual de uma ontologia permite o desenvolvimento de interfaces dinâmicas e interativas, proporcionando ao usuário uma navegação estimulante e prazerosa por entre os documentos resultantes de sua busca, tendo por base os termos de uma determinada área de conhecimento.
An information retrieval system is a mediating element between a document collection and the users who looking for relevant documents. In this context, interfaces play an important role: firstly, assisting the user to expressing their information need by means of a search expression, and secondly by providing resources to help selecting relevant documents from the obtained results. The information retrieval is a linguistic process whose efficiency depends on terminological coincidences between the user’s query and the representation of documents. This work proposes an interface model in which the terminological structure of an ontology is used to assist the user in the selection of relevant documents among those resulting from their search. It is characterized as an applied, exploratory and bibliographic research. It is concluded that the visual presentation of ontology allows the development of dynamic and interactive interfaces, providing the user with stimulating and pleasant navigation among the documents resulting from their search, based on the terms of a certain knowledge area.
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Rouquet, David. "Multilinguisation d'ontologies dans le cadre de la recherche d'information translingue dans des collections d'images accompagnées de textes spontanés." Phd thesis, Université de Grenoble, 2012. http://tel.archives-ouvertes.fr/tel-00743652.
Full textAbstract:
Le Web est une source proliférante d'objets multimédia, décrits dans différentes langues natu- relles. Afin d'utiliser les techniques du Web sémantique pour la recherche de tels objets (images, vidéos, etc.), nous proposons une méthode d'extraction de contenu dans des collections de textes multilingues, paramétrée par une ou plusieurs ontologies. Le processus d'extraction est utilisé pour indexer les objets multimédia à partir de leur contenu textuel, ainsi que pour construire des requêtes formelles à partir d'énoncés spontanés. Il est basé sur une annotation interlingue des textes, conservant les ambiguïtés de segmentation et la polysémie dans des graphes. Cette première étape permet l'utilisation de processus de désambiguïsation "factorisés" au niveau d'un lexique pivot (de lexèmes interlingues). Le passage d'une ontologie en paramètre du système se fait en l'alignant de façon automatique avec le lexique interlingue. Il est ainsi possible d'utiliser des ontologies qui n'ont pas été conçues pour une utilisation multilingue, et aussi d'ajouter ou d'étendre l'ensemble des langues et leurs couvertures lexicales sans modifier les ontologies. Un démonstrateur pour la recherche multilingue d'images, développé pour le projet ANR OMNIA, a permis de concrétiser les approches proposées. Le passage à l'échelle et la qualité des annotations produites ont ainsi pu être évalués.