This study examines the importance of relevance criteria in end-user evaluation of valuable or high relevant information.

The World Wide Web is one of the largest sources of information; more and more applications are being developed daily to make use of this information. This thesis presents a multi-agent architecture that deals with some of the issues related to Internet data extraction. The primary issue addresses the reliable, efficient and quick extraction of data through the use of HTTP performance monitoring agents. A second issue focuses on how to make use of available data to take decisions and alert the user when there is change in data; this is done with the help of user agents that are equipped with a Defeasible reasoning interpreter. An additional issue is the visualization of extracted data; this is done with the aid of VRML visualization agents. The cited issues are discussed using stock portfolio management as an example application.

We build a joint multimodal model of text and images for automatically assigning illustrative images to journalistic articles. We approach the task as an unsupervised representation learning problem of finding a common representation that abstracts from individual modalities, inspired by multimodal Deep Boltzmann Machine of Srivastava and Salakhutdinov. We use state-of-the-art image content classification features obtained from the Convolutional Neural Network of Krizhevsky et al. as input "images" and entire documents instead of keywords as input texts. A deep learning and experiment management library Safire has been developed. We have not been able to create a successful retrieval system because of difficulties with training neural networks on the very sparse word observation. However, we have gained substantial understanding of the nature of these difficulties and thus are confident that we will be able to improve in future work.

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

Syftet med denna uppsats är att undersöka hur väl Google Translate respektive Bing Translator fungerar vid översättning av sökfrågor med avseende på svenska sammansättningar, samt försöka utröna huruvida det finns något samband mellan utfallet och sammansättningarnas komplexitet. Testmiljön utgörs av Europaparlamentets offentliga dokumentregister. Undersökningen är emellertid begränsad till Europeiska rådets handlingar, som till antalet är 1 334 på svenska respektive 1 368 på engelska. Analysen av data har dels skett utifrån precision och återvinningsgrad, dels utifrån en kontrastiv analys för att kunna ge en mer enhetlig bild på det undersökta fenomenet. Resultatet visar att medelvärdet varierar mellan 0,287 och 0,506 för precision samt 0,400 och 0,614 för återvinningsgrad beroende på ordtyp och översättningstjänst. Vidare visar resultatet att det inte tycks finnas något tydligt samband mellan effektivitet och sammansättningarnas komplexitet. I stället tycks de lägre värdena bero på synonymi, och då gärna inom själva sammansättningen, samt hyponymi. I det senare fallet beror det dels på översättningstjänsternas oförmåga att återge lämpliga översättningar, dels på det engelska språkets tendens att bilda sammansättningar med lösa substantivattribut.

Coleções de músicas estão amplamente disponíveis na internet e, graças ao crescimento na capacidade de armazenamento e velocidade de transmissão de dados, usuários podem ter acesso a uma quantidade quase ilimitada de composições. Isso levou a uma maior necessidade de organizar, recuperar e processar dados musicais de modo automático. Visualização de informação é uma área de pesquisa que possibilita a análise visual de grandes conjuntos de dados e, por isso, é uma ferramenta muito valiosa para a exploração de bibliotecas musicais. Nesta dissertação, metodologias para a construção de duas técnicas de visualização de bases de dados de música são propostas. A primeira, Grafo de Similaridades, permite a exploração da base de dados em termos de similaridades hierárquicas. A segunda, RadViz Concêntrico, representa os dados em termos de tarefas de classificação e permite que o usuário altere a visualização de acordo com seus interesses. Ambas as técnicas são capazes de revelar estruturas de interesse no conjunto de dados, facilitando o seu entendimento e exploração. / Music collections are widely available on the internet and, leveraged by the increasing storage and bandwidth capability, users can currently access a multitude of songs. This leads to a growing demand towards automated methods for organizing, retrieving and processing music data. Information visualization is a research area that allows the analysis of large data sets, thus, it is a valuable tool for the exploration of music libraries. In this thesis, methodologies for the development of two music visualization techniques are proposed. The first, Similarity Graph, enables the exploration of data sets in terms of hierarchical similarities. The second, Concentric RadViz, represents the data in terms of classification tasks and enables the user to alter the visualization according to his interests. Both techniques are able to reveal interesting structures in the data, favoring its understanding and exploration.

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.

Yu Kwok Leung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1999. / Includes bibliographical references (leaves 91-96). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- The Problem --- p.1 / Chapter 1.2 --- Information Filtering --- p.2 / Chapter 1.3 --- Contributions --- p.7 / Chapter 1.4 --- Organization Of The Thesis --- p.10 / Chapter 2 --- Related Work --- p.12 / Chapter 3 --- Adaptive Text Filtering --- p.22 / Chapter 3.1 --- Representation --- p.22 / Chapter 3.1.1 --- Textual Document --- p.23 / Chapter 3.1.2 --- Filtering Profile --- p.28 / Chapter 3.2 --- On-line Learning Algorithms For Adaptive Text Filtering --- p.29 / Chapter 3.2.1 --- The Sleeping Experts Algorithm --- p.29 / Chapter 3.2.2 --- The EG-based Algorithms --- p.32 / Chapter 4 --- The REPGER Algorithm --- p.37 / Chapter 4.1 --- A New Approach --- p.37 / Chapter 4.2 --- Relevance Prediction By RElevant feature Pool --- p.42 / Chapter 4.3 --- Retrieving Good Training Examples --- p.45 / Chapter 4.4 --- Learning Dissemination Threshold Dynamically --- p.49 / Chapter 5 --- The Threshold Learning Algorithm --- p.50 / Chapter 5.1 --- Learning Dissemination Threshold Dynamically --- p.50 / Chapter 5.2 --- Existing Threshold Learning Techniques --- p.51 / Chapter 5.3 --- A New Threshold Learning Algorithm --- p.53 / Chapter 6 --- Empirical Evaluations --- p.55 / Chapter 6.1 --- Experimental Methodology --- p.55 / Chapter 6.2 --- Experimental Settings --- p.59 / Chapter 6.3 --- Experimental Results --- p.62 / Chapter 7 --- Integrating With Feature Clustering --- p.76 / Chapter 7.1 --- Distributional Clustering Algorithm --- p.79 / Chapter 7.2 --- Integrating With Our REPGER Algorithm --- p.82 / Chapter 7.3 --- Empirical Evaluation --- p.84 / Chapter 8 --- Conclusions --- p.87 / Chapter 8.1 --- Summary --- p.87 / Chapter 8.2 --- Future Work --- p.88 / Bibliography --- p.91 / Chapter A --- Experimental Results On The AP Corpus --- p.97 / Chapter A.1 --- The EG Algorithm --- p.97 / Chapter A.2 --- The EG-C Algorithm --- p.98 / Chapter A.3 --- The REPGER Algorithm --- p.100 / Chapter B --- Experimental Results On The FBIS Corpus --- p.102 / Chapter B.1 --- The EG Algorithm --- p.102 / Chapter B.2 --- The EG-C Algorithm --- p.103 / Chapter B.3 --- The REPGER Algorithm --- p.105 / Chapter C --- Experimental Results On The WSJ Corpus --- p.107 / Chapter C.1 --- The EG Algorithm --- p.107 / Chapter C.2 --- The EG-C Algorithm --- p.108 / Chapter C.3 --- The REPGER Algorithm --- p.110

Kwok Chi Leong. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 122-127). / Abstracts in English and Chinese. / Abstract --- p.ii / Acknowledgment --- p.vi / Table of Contents --- p.vii / List of Tables --- p.x / List of Figures --- p.xi / Chapter Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Contributions --- p.2 / Chapter 1.2 --- Thesis Overview --- p.3 / Chapter Chapter 2 --- Background Information --- p.5 / Chapter 2.1 --- Documents Clustering --- p.5 / Chapter 2.1.1 --- Review of Clustering Techniques --- p.5 / Chapter 2.1.2 --- Suffix Tree Clustering --- p.7 / Chapter 2.2 --- Chinese Information Processing --- p.8 / Chapter 2.2.1 --- Sentence Segmentation --- p.8 / Chapter 2.2.2 --- Keyword Extraction --- p.10 / Chapter Chapter 3 --- The Generic Chinese PAT Tree --- p.12 / Chapter 3.1 --- PAT Tree --- p.13 / Chapter 3.1.1 --- Patricia Tree --- p.13 / Chapter 3.1.2 --- Semi-Infinite String --- p.14 / Chapter 3.1.3 --- Structure of Tree Nodes --- p.17 / Chapter 3.1.4 --- Some Examples of PAT Tree --- p.22 / Chapter 3.1.5 --- Storage Complexity --- p.24 / Chapter 3.2 --- The Chinese PAT Tree --- p.26 / Chapter 3.2.1 --- The Chinese PAT Tree Structure --- p.26 / Chapter 3.2.2 --- Some Examples of Chinese PAT Tree --- p.30 / Chapter 3.2.3 --- Storage Complexity --- p.33 / Chapter 3.3 --- The Generic Chinese PAT Tree --- p.34 / Chapter 3.3.1 --- Structure Overview --- p.34 / Chapter 3.3.2 --- Structure of Tree Nodes --- p.35 / Chapter 3.3.3 --- Essential Node --- p.37 / Chapter 3.3.4 --- Some Examples of the Generic Chinese PAT Tree --- p.41 / Chapter 3.3.5 --- Storage Complexity --- p.45 / Chapter 3.4 --- Problems of Embedded Nodes --- p.46 / Chapter 3.4.1 --- The Reduced Structure --- p.47 / Chapter 3.4.2 --- Disadvantages of Reduced Structure --- p.48 / Chapter 3.4.3 --- A Case Study of Reduced Design --- p.50 / Chapter 3.4.4 --- Experiments on Frequency Mismatch --- p.51 / Chapter 3.5 --- Strengths of the Generic Chinese PAT Tree --- p.55 / Chapter Chapter 4 --- Performance Analysis on the Generic Chinese PAT Tree --- p.58 / Chapter 4.1 --- The Construction of the Generic Chinese PAT Tree --- p.59 / Chapter 4.2 --- Counting the Essential Nodes --- p.61 / Chapter 4.3 --- Performance of Various PAT Trees --- p.62 / Chapter 4.4 --- The Implementation Analysis --- p.64 / Chapter 4.4.1 --- Pure Dynamic Memory Allocation --- p.64 / Chapter 4.4.2 --- Node Production Factory Approach --- p.66 / Chapter 4.4.3 --- Experiment Result of the Factory Approach --- p.68 / Chapter Chapter 5 --- The Chinese Documents Clustering --- p.70 / Chapter 5.1 --- The Clustering Framework --- p.70 / Chapter 5.1.1 --- Documents Cleaning --- p.73 / Chapter 5.1.2 --- PAT Tree Construction --- p.76 / Chapter 5.1.3 --- Essential Node Extraction --- p.77 / Chapter 5.1.4 --- Base Clusters Detection --- p.80 / Chapter 5.1.5 --- Base Clusters Filtering --- p.86 / Chapter 5.1.6 --- Base Clusters Combining --- p.94 / Chapter 5.1.7 --- Documents Assigning --- p.95 / Chapter 5.1.8 --- Result Presentation --- p.96 / Chapter 5.2 --- Discussion --- p.96 / Chapter 5.2.1 --- Flexibility of Our Framework --- p.96 / Chapter 5.2.2 --- Our Clustering Model --- p.97 / Chapter 5.2.3 --- More About Clusters Detection --- p.98 / Chapter 5.2.4 --- Analysis and Complexity --- p.100 / Chapter Chapter 6 --- Evaluations on the Chinese Documents Clustering --- p.101 / Chapter 6.1 --- Details of Experiment --- p.101 / Chapter 6.1.1 --- Parameter of Weighted Frequency --- p.105 / Chapter 6.1.2 --- Effect of CLP Analysis --- p.105 / Chapter 6.1.3 --- Result of Clustering --- p.108 / Chapter 6.2 --- Clustering on Larger Collection --- p.109 / Chapter 6.2.1 --- Comparing the Base Clusters --- p.109 / Chapter 6.2.2 --- Result of Clustering --- p.111 / Chapter 6.2.3 --- Discussion --- p.112 / Chapter 6.3 --- Clustering with Part of Documents --- p.113 / Chapter 6.3.1 --- Clustering with News Headlines --- p.114 / Chapter 6.3.2 --- Clustering with News Abstract --- p.117 / Chapter Chapter 7 --- Conclusion --- p.119 / Bibliography --- p.122

Low Kon Fan. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1998. / Includes bibliographical references (leaves 165-168). / Abstract also in Chinese. / Abstract --- p.i / Acknowledgment --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Overview of Information Filtering --- p.1 / Chapter 1.2 --- Contributions --- p.4 / Chapter 1.3 --- Organization of this thesis --- p.6 / Chapter 2 --- Existing Approaches --- p.7 / Chapter 2.1 --- Representational issues --- p.7 / Chapter 2.1.1 --- Document Representation --- p.7 / Chapter 2.1.2 --- Feature Selection --- p.11 / Chapter 2.2 --- Traditional Approaches --- p.15 / Chapter 2.2.1 --- NewsWeeder --- p.15 / Chapter 2.2.2 --- NewT --- p.17 / Chapter 2.2.3 --- SIFT --- p.19 / Chapter 2.2.4 --- InRoute --- p.20 / Chapter 2.2.5 --- Motivation of Our Approach --- p.21 / Chapter 2.3 --- Probabilistic Approaches --- p.23 / Chapter 2.3.1 --- The Naive Bayesian Approach --- p.25 / Chapter 2.3.2 --- The Bayesian Independence Classifier Approach --- p.28 / Chapter 2.4 --- Comparison --- p.31 / Chapter 3 --- Our Bayesian Network Approach --- p.33 / Chapter 3.1 --- Backgrounds of Bayesian Networks --- p.34 / Chapter 3.2 --- Bayesian Network Induction Approach --- p.36 / Chapter 3.3 --- Automatic Construction of Bayesian Networks --- p.38 / Chapter 4 --- Automatic Feature Discretization --- p.50 / Chapter 4.1 --- Predefined Level Discretization --- p.52 / Chapter 4.2 --- Lloyd's algorithm . . > --- p.53 / Chapter 4.3 --- Class Dependence Discretization --- p.55 / Chapter 5 --- Experiments and Results --- p.59 / Chapter 5.1 --- Document Collections --- p.60 / Chapter 5.2 --- Batch Filtering Experiments --- p.63 / Chapter 5.3 --- Batch Filtering Results --- p.65 / Chapter 5.4 --- Incremental Session Filtering Experiments --- p.87 / Chapter 5.5 --- Incremental Session Filtering Results --- p.88 / Chapter 6 --- Conclusions and Future Work --- p.105 / Appendix A --- p.107 / Appendix B --- p.116 / Appendix C --- p.126 / Appendix D --- p.131 / Appendix E --- p.145