O avanço da tecnologia nos últimos anos permitiu a criação de Sistemas de Informação com acesso a grandes bases de dados, abrindo diversas possibilidades de aplicações. Tem-se como exemplo a Internet, onde uma enorme quantidade de dados é gerada e publicada a todo momento por usuários ao redor do mundo. Com isso, aos poucos foi surgindo a necessidade de métodos para filtrar o conteúdo disponível de forma a permitir que um usuário pudesse focar apenas nos seus interesses. Nesse contexto surgiram os Sistemas de Recomendação e as Redes Sociais, onde, mais recentemente, surgiram trabalhos que apresentam abordagens para o uso de Sistemas de Recomendação no contexto acadêmico, de forma a aumentar a produtividade de grupos de pesquisa. Também têm sido bastante exploradas formas de se utilizar informações temporais em Sistemas de Recomendação de maneira a melhorar as recomendações feitas. O presente trabalho propõe uma abordagem de recomendação de colaborações acadêmicas utilizando a técnica de Análise de Séries Temporais, buscando melhorar os resultados obtidos por trabalhos anteriores. Foi realizado um experimento offline para avaliar o desempenho da abordagem proposta em relação às abordagens anteriores e um estudo de usuários para fazer uma análise mais profunda com feedback de usuários. Foram utilizadas métricas conhecidas das áreas de Recuperação de Informação e Sistemas de Recomendação, mas alguns resultados se mostraram inferiores em comparação com as abordagens existentes; outros, porém, foram similares. Também foram utilizadas algumas métricas de avaliação focadas em Sistemas de Recomendação, e os resultados obtidos foram similares em todas as abordagens testadas. / The advance of technology in recent years made possible the creation of Information Systems with access to large databases, opening many applications possibilities. There’s the Internet, for example, where a vast amount of data is generated and published all the time by users around the world. In this sense, the need for methods to filter the available content to enable users to focus only on their interests slowly emerged. In this context, Recommender Systems and Social Networks appeared, where, recently, works reporting approaches to provide recommendations in the academic context appeared, increasing the productivity of research groups. New ways to employ temporal information in Recommender Systems to make better recommendations are also being explored. The present work proposes an approach to academic collaborations recommendation using Time Series Analysis, aiming to improve results reported on previous and current works. An offline experiment was done to evaluate the proposed approach in comparison with other works and a user study was done to make a deeper analysis from user feedback. Known metrics from the Information Retrieval and Recommender Systems fields were used, and in some cases the results obtained were lower compared to the current methods but similar in others. Some evaluation metrics from Recommender Systems were also used, and the results were similar to all approaches.

In today's significant and rapidly increasing amount of scientific publications, exploring recent studies in a given research area and building an effective scientific collaboration has become more challenging than any time before. Scientific production growth has been increasing the difficulties for identifying the most relevant papers to cite or to find an appropriate conference or journal to submit a paper to publish. As a result, authors and publishers rely on different analytical approaches in order to measure the relationship among the citation network. Different parameters have been used such as the impact factor, number of citations, co-citation to assess the impact of the produced research publication. However, using one assessing factor considers only one level of relationship exploration, since it does not reflect the effect of the other factors. In this thesis, we propose an approach to measure the Academic Citation Impact that will help to identify the impact of articles, authors, and venues at their extended nearby citation network. We combine the content similarity with the bibliometric indices to evaluate the citation impact of articles, authors, and venues in their surrounding citation network. Using the article metadata, we calculate the semantic similarity between any two articles in the extended network. Then we use the similarity score and bibliometric indices to evaluate the impact of the articles, authors, and venues among their extended nearby citation network. Furthermore, we propose an academic recommendation model to identify the latent preferences among the citation network of the given article in order to expose the concealed connection between the academic objects (articles, authors, and venues) at the citation network of the given article. To reveal the degree of trust for collaboration between academic objects (articles, authors, and venues), we use the similarity learning to estimate the collaborative confidence score that represents the anticipation of a prospect relationship between the academic objects among a scientific community. We conducted an offline experiment to measure the accuracy of delivering personalized recommendations, based on the user’s selection preferences; real-world datasets were used. Our evaluation results show a potential improvement to the quality of the recommendation when compared to baseline recommendation algorithms that consider co-citation information.

In 2011, the United Kingdom (U.K.) physical activity (PA) guidelines were updated. The adult moderate-to-vigorous intensity PA (MVPA) recommendation changed to reflect that different frequency and intensity permutations lead to equivalent health benefits. New recommendations were added for muscle strengthening activities (MSA) and the reduction of sedentary time (ST). Those over 65 years were also recommended to undertake balance and co-ordination activities (BCA). Despite these new additions, Scottish PA policy still concentrated on MVPA, with considerable resources allocated to sport and some exercise activities. Since 2012, the Scottish Health Survey (SHeS) has collected data relating to these new recommendations annually, but few analyses have been undertaken. This thesis contains the most comprehensive analyses of the 2012-15 SHeS PA and ST data to date, and a review into whether the method produces valid and reliable estimates. The aim of this thesis was to inform Scottish PA and sedentary behaviour policy by producing research to support the incorporation of these new recommendations and the promotion of non-sport-related MVPA policies. It also aimed to inform any future developments to PA and ST surveillance in Scotland. The first three studies of this thesis are cross-sectional analyses of the updated recommendations for adults in Scotland. They present prevalence and participation data in specific domains, activities, and behaviours by age and sex. The main findings were that (1) sport was a minority contributor to the total MVPA of adults in Scotland, regardless of sex, age, or activity status (never more than 20%), (2) compliance with the MSA recommendation was approximately half that of the MVPA recommendation (31% of men and 24% of women), and compliance with the BCA recommendation amongst those over 65 years was very low (19% of older men and 12% of older women), and (3) middle-aged adults in work reported a comparable amount of weekday ST to adults over 75 years (7-8 hours per day). The fourth study was a review of the available evidence into whether the PA and ST estimates produced by the 2012-15 SHeS were valid and reliable. The SHeS was found to be fit for purpose, but recommendations were made regarding the analysis and interpretation of the data to minimise areas of concern. These were (1) analyse MVPA data with and without the domain of occupational MVPA, (2) make it clear that only sport and exercise activities can contribute to achieving the MSA and BCA recommendations under the SHeS method, and (3) focus on the comparisons between groups in relation to ST, rather than on the absolute values. The fifth study used the findings from the previous four to inform the design of a prospective cohort study that will investigate the joint effects of MVPA and total ST on all-cause mortality, cardiovascular disease, cancer, and diabetes. This thesis contains the results of the preliminary analyses. This study is designed to inform policy by providing novel information on how the combination of these behaviours affects health outcomes in a representative sample of Scottish adults. There is clear evidence that this work has already informed policy and surveillance. The work on the relative contribution of the domains of MVPA is regularly cited in evidence briefings for the Scottish Government and the Scottish Parliament. This has increased the awareness amongst key policy-makers that sport is not a major contributor to the total MVPA of adults in Scotland. The work on MSA, BCA, and ST was a catalyst for a proposal to include indicators relating to these recommendations on the national PA monitoring framework. The work on MSA and BCA has also been a key reference text in preparation for the next update to the U.K. PA guidelines, stressing the need to consider surveillance at an early stage. In summary, the novel analyses of SHeS data undertaken for this thesis have demonstrably informed PA and sedentary behaviour policy and surveillance in Scotland.

Made available in DSpace on 2016-12-23T14:07:26Z (GMT). No. of bitstreams: 1 Pedro Paulo Favato Barcelos Cap 1 a 5.pdf: 1996678 bytes, checksum: 06570d7feadc8f768039f34ccc71400a (MD5) Previous issue date: 2011-04-07 / A recomendação ITU-T G.805 (ITU-T, 2000) é uma importante recomendação para redes de transporte, pois descreve uma arquitetura funcional genérica independente de tecnologias para este domínio e é usada como base para outras recomendações que descrevem a arquitetura funcional de redes, a gerência, a avaliação de desempenho e a especificação funcional de equipamentos. Apesar de fornecer uma ferramenta ágil para a descrição da arquitetura, a apresentação dos conceitos é feita de forma textual, gerando confusão por conta de definições recursivas e exemplos não claros, que muitas vezes até mesmo se contradizem. Esses aspectos da recomendação a torna de difícil entendimento, podendo confundir o leitor. É importante que, devido sua fundamental relevância, essa recomendação seja livre desses problemas. Para tal, é proposta nesta dissertação a utilização de técnicas de modelagem conceitual baseadas em ontologias para a geração de um modelo de referência para a área de redes de transporte, a partir da Recomendação ITU-T G.805. Além dos principais conceitos da recomendação são também apresentadas as vantagens da criação de um modelo de referência em ontologias e as principais tecnologias utilizadas para este objetivo. São realizadas uma análise arquitetural e uma reestruturação dos componentes definidos pela recomendação e uma avaliação ontológica da mesma, verificando casos de incompletudes, ambiguidades e outras deficiências ontológicas e apontando soluções. Por fim, é apresentado o modelo de referência em ontologia desenvolvido para a Recomendação ITU-T G.805, incluindo o modelo conceitual e suas regras de derivação e de restrição / The ITU-T Recommendation G.805 (ITU-T, 2000) is an important recommendation for transport networks. It describes a generic functional architecture that is independent of technology for this domain and it is used as the basis for recommendations that describe the functional architecture of networks, management, performance analysis and functional specification of equipment. Despite providing a flexible tool for the architecture description, the recommendation presents its concepts textually, leading to confusion because of recursive definitions and unclear examples that are often contradictory. These aspects of the recommendation make it difficult to understand and may confuse the reader. It is important that, due to its fundamental importance, this recommendation is free from these problems. For this purpose, this work proposes the use of ontology-based conceptual modeling techniques for the generation of a reference model for the transport network domain, based on the ITU-T Recommendation G.805. In addition to the recommendation main concepts, the advantages of creating an ontology-based reference model and the main technologies used for this purpose are also presented. An architectural analysis and a restructuring of the components defined by the recommendation are performed together with an ontological evaluation of it. Cases of incompleteness, ambiguities and other deficiencies are checked and solutions are pointed. Finally, the ontology-based reference model developed for the ITU-T Recommendation G.805 is presented, including the conceptual model and its derivation and restrictions rules

Submitted by PAULA REGINA VENTURA AMORIM GONÇALEZ null (paulaventuramorim@gmail.com) on 2017-03-30T15:23:10Z No. of bitstreams: 1 Gonçalez_tese.pdf: 1534958 bytes, checksum: 60a0a3040867106b3071326928618a5e (MD5) / Approved for entry into archive by Luiz Galeffi (luizgaleffi@gmail.com) on 2017-03-30T16:53:40Z (GMT) No. of bitstreams: 1 goncalez_prva_dr_mar.pdf: 1534958 bytes, checksum: 60a0a3040867106b3071326928618a5e (MD5) / Made available in DSpace on 2017-03-30T16:53:40Z (GMT). No. of bitstreams: 1 goncalez_prva_dr_mar.pdf: 1534958 bytes, checksum: 60a0a3040867106b3071326928618a5e (MD5) Previous issue date: 2017-03-06 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / As Instituições Arquivísticas são desafiadas a constante atualização no uso das Tecnologias de Informação e Comunicação (TIC) para organizar, preservar e disponibilizar de maneira confiável seu acervo documental que é gerado em grandes quantidades e em diferentes suportes. Na atualidade, os acervos arquivísticos são híbridos, isto é, são compostos por documentos nascidos digitais, digitais e analógicos. Isso exige das instituições a otimização de seus serviços, ainda mais no que se refere ao atendimento ao usuário que almeja ter satisfeitas suas necessidades informacionais de maneira fácil, rápida e segura. Nesse cenário, o objetivo deste trabalho é analisar o conjunto de atributos essenciais para a implantação de Repositórios Arquivísticos Digitais Confiáveis (RDC-Arq) e a vinculação do arquivista como membro integrante de uma equipe de trabalho na orientação dos requisitos com ênfase ao acesso à informação. Optou-se como procedimento metodológico pelo estudo teórico fundamentado nos princípios da Arquivologia. A etapa exploratória é realizada a partir da análise da Resolução 39 do CONARQ (Diretrizes para a implementação de Repositórios Arquivísticos Digitais Confiáveis RDC-Arq) e da ISO 16363:2012 (Space data and information transfer systems -- Audit and certification of trustworthy digital repositories) que fazem recomendações técnicas para serem utilizadas como base para que repositórios digitais sejam certificados confiáveis ou que possibilitem a medição da confiabilidade do repositório. Os resultados apresentam as ações do arquivista para o acesso a documentos e informações arquivísticas e o cotejamento entre a Norma ISO 16363:2012 e a Recomendação 39 do CONARQ. Assim, o estudo resultou em um conjunto de recomendações para a certificação de Repositórios Arquivísticos Digitais com um recorte focado na identificação de requisitos com ênfase no acesso à informação. Por fim, é apresentado um conjunto de informações para que o arquivista possa fazer a medição da certificação de confiabilidade de um repositório digital ou para solicitar sua certificação de confiabilidade. / Archival institutions are constantly challenged to update the use of Information and Communication Technologies (ICT) to reliably organize, preserve and provide their document collections that are generated in large quantity and in different media. Currently, the archival collections are hybrids, ie they are composed of documents that were originally digital, converted to digital, and analog. This requires that the institutions optimize their services, especially as regards to service to the user who aims to have his / her information needs satisfied easily, quickly and safely. In this scenario, the objective of this study is to analyze the set of essential attributes for the deployment of Trusted Digital Archival Repositories (TDARs) and the linking of the archivist as a member of a work team in guiding the requirements with emphasis on access to information. The methodological procedure was chosen by theoretical study grounded on the principles of Archivology. The exploratory stage is carried out from the analysis of Resolution 39 of CONARQ (Guidelines for the implementation of Trusted Digital Archival Repositories TDARs) and ISO 16363: 2012 (Space data and information transfer systems - Audit and certification of trustworthy digital repositories) that make technical recommendations used as a basis for digital repositories being certified as reliable or allow the measurement of repository reliability. The results present the archivist's actions for access to archival documents and information and the comparison between ISO 16363: 2012 and Recommendation 39 of CONARQ. Thus, the study resulted in a set of recommendations for certification of Digital Archival Repositories with a focus on identifying requirements with an emphasis on access to information. Finally, a set of information is presented so that the archivist can measure reliability of the certification of a digital repository or ask for its reliability certification.

This diploma thesis addresses one of the modern marketing communication tools -- event marketing whose importance is steeply growing in these days not only abroad but also in the Czech Republic. The objective of this work is to analyze certain problems associated with event marketing involvement in the marketing communication mix of a company occurring in the business-to-business sector. The first part of the work is devoted to the theoretical introduction to different issues around event marketing. However, its main content is created by a view of the situation of the particular company -- MECAS ESI s.r.o. In this part I put emphasis on three event types, using them to carry out a deeper analysis with the aim to reveal their essential problems and to propose certain recommendations to the future. Regarding the applied methods, I use especially structured interviews with particular members of the company, further I gain some information also from a questionnaire survey carried out among event attendees and finally I complete these results with my own knowledge and experience from the company's environment. In the end I come to the conclusion that most of the problems are caused by the insufficient level of cooperation between the sales and marketing department.

L'évolution rapide du web a changé la façon dont l'information est créée, distribuée, évaluée et consommée. L'utilisateur est dorénavant mis au centre du web en devenant le générateur de contenu le plus prolifique. Pour évoluer dans le flot d'informations, les utilisateurs ont besoin de filtrer le contenu en fonction de leurs centres d'intérêts. Pour bénéficier de contenus personnalisés, les utilisateurs font appel aux réseaux sociaux ou aux systèmes de recommandations exploitant leurs informations privées. Cependant, ces systèmes posent des problèmes de passage à l'échelle, ne prennent pas en compte la nature dynamique de l'information et soulèvent de multiples questions d'un point de vue de la vie privée. Dans cette thèse, nous exploitons les architectures pair-à-pair pour implémenter des systèmes de recommandations pour la dissémination personnalisée des news. Une approche pair-à-pair permet un passage à l'échelle naturel et évite qu'une entité centrale contrôle tous les profils des utilisateurs. Cependant, l'absence de connaissance globale fait appel à des schémas de filtrage collaboratif qui doivent palier les informations partielles et dynamiques des utilisateurs. De plus, ce schéma de filtrage doit pouvoir respecter la vie privée des utilisateurs. La première contribution de cette thèse démontre la faisabilité d'un système de recommandation de news totalement distribué. Le système proposé maintient dynamiquement un réseau social implicit pour chaque utilisateur basé sur les opinions qu'il exprime à propos des news reçues. Les news sont disséminées au travers d'un protocole épidémique hétérogène qui (1) biaise l'orientation des cibles et (2) amplifie la dissémination de chaque news en fonction du niveau d'intérêt qu'elle suscite. Ensuite, pour améliorer la vie privée des utilisateurs, nous proposons des mécanismes d'offuscation permettant de cacher le profil exact des utilisateurs sans trop dégrader la qualité de la recommandation fournie. Enfin, nous explorons un nouveau modèle tirant parti des avantages des systèmes distribués tout en conservant une architecture centralisée. Cette solution hybride et générique permet de démocratiser les systèmes de recommandations en offrant aux fournisseurs de contenu un système de personnalisation à faible coût. / The rapid evolution of the web has changed the way information is created, distributed, evaluated and consumed. Users are now at the center of the web and becoming the most prolific content generators. To effectively navigate through the stream of available news, users require tools to efficiently filter the content according to their interests. To receive personalized content, users exploit social networks and recommendation systems using their private data. However, these systems face scalability issues, have difficulties in coping with interest dynamics, and raise a multitude of privacy challenges. In this thesis, we exploit peer-to-peer networks to propose a recommendation system to disseminate news in a personalized manner. Peer-to-peer approaches provide highly-scalable systems and are an interesting alternative to Big brother type companies. However, the absence of any global knowledge calls for collaborative filtering schemes that can cope with partial and dynamic interest profiles. Furthermore, the collaborative filtering schemes must not hurt the privacy of users. The first contribution of this thesis conveys the feasibility of a fully decentralized news recommender. The proposed system constructs an implicit social network based on user profiles that express the opinions of users about the news items they receive. News items are disseminated through a heterogeneous gossip protocol that (1) biases the orientation of the dissemination, and (2) amplifies dissemination based on the level of interest in each news item. Then, we propose obfuscation mechanisms to preserve privacy without sacrificing the quality of the recommendation. Finally, we explore a novel scheme leveraging the power of the distribution in a centralized architecture. This hybrid and generic scheme democratizes personalized systems by providing an online, cost-effective and scalable architecture for content providers at a minimal investment cost.

Submitted by Rosivalda Pereira (mrs.pereira@ufma.br) on 2017-08-16T17:52:50Z No. of bitstreams: 1 RodrigoFeitosa.pdf: 4009932 bytes, checksum: 55ef5e97ddc653cf1849e17eafdc396f (MD5) / Made available in DSpace on 2017-08-16T17:52:50Z (GMT). No. of bitstreams: 1 RodrigoFeitosa.pdf: 4009932 bytes, checksum: 55ef5e97ddc653cf1849e17eafdc396f (MD5) Previous issue date: 2013-03-22 / The search of knowledge and its manipulation in companies, institutions or other organizations has become a challenge nowadays. Mostly due to two aspects: the large volume of information available and the difficulty in extracting the knowledge proper to each person (intellectual capital). This difficulty becomes more accentuated when the scenario involved the extraction of knowledge is the Web. The area of Knowledge Management seeks a solution to the limitations described above. Techniques for extracting and control of knowledge can be adopted with the use of Artificial Intelligence, particularly the Knowledge Discovery in Databases. This work proposes the creation of a methodology and application that perform the Data Mining with textual information linked to geo data in a social network, in order to promote Social Recommendation. However, approaches in building recommendation systems present some shortcomings in filtering the results and the way they are suggested to users. The research aims to remedy these deficiencies and addresses issues that still need to search more effective and consolidated results. / A busca do conhecimento e a sua manipulação em empresas, instituições ou outras organizações tem se tornado um desafio nos dias atuais. Em grande parte devido a dois aspectos: o grande volume de informação disponibilizada e a dificuldade em extrair o conhecimento próprio de cada pessoa (capital intelectual). Essa dificuldade torna-se mais acentuada quando o cenário envolvido para a extração de conhecimento é a Web. A área da Gestão de Conhecimento busca a solução para as limitações descritas anteriormente. Técnicas para a extração e controle do conhecimento podem ser adotadas com o uso da Inteligência Artificial, sobretudo a Descoberta de Conhecimento em Bases de Dados. Este trabalho propõe-se a criação de uma metodologia e aplicação que realize a Mineração de Dados com informações textuais vinculados a dados geolocalizados em uma Rede Social, com o intuito de promover a Recomendação Social. Entretanto, as abordagens na construção dos Sistemas de Recomendação apresentam algumas deficiências na filtragem dos resultados e na forma que estes são sugeridos aos usuários. A pesquisa busca a solução destas deficiências e aborda temas que ainda carecem de pesquisas mais efetivas e resultados consolidados.

Como os interagentes selecionam conteúdo sob a influência dos sistemas de recomendação digital é o problema de pesquisa apresentado nesta tese. A abundância de dados nos repositórios digitais exige sistemas de recuperação de informação eficazes para auxiliar o usuário na gestão e na seleção de itens de informação. Desta forma, o objetivo geral deste trabalho pretende investigar o comportamento dos interagentes na seleção de itens frente ao sistema de recomendação digital do website da loja virtual Amazon. O sistema de recomendação da Amazon foi investigado com a intenção de se compreender como o usuário utiliza um sistema automatizado de listas de referências em forma de recomendação de conteúdo. O funcionamento dos sistemas de recomendação é fundamentado com a proposta de conhecer suas características e funcionalidades. Como o problema de pesquisa tem em sua temática a recomendação de itens de informação, tornou-se necessário compreender como os usuários interagem com os sistemas para perceber como as recomendações são feitas. O aporte teórico desta pesquisa aproxima os estudos dos campos da Informação e da Comunicação. As técnicas de pesquisas aplicadas envolvem métodos de pesquisa qualitativa. Ao distinguir as recomendações a partir das interações reativas e mútuas dos usuários, propõe-se nesta tese a Matriz de Recomendações de Itens de Informação constituída pelos seguintes quadrantes: Recomendações Objetivas Digitais; Recomendações Subjetivas Digitais; Recomendações Objetivas Analógicas e Recomendações Subjetivas Analógicas. Digitais; Recomendações Objetivas Analógicas e Recomendações Subjetivas Analógicas. Para analisar o comportamento dos interagentes no uso dessas recomendações, a estratégia metodológica aplicou entrevista em profundidade e observação direta. Os resultados desta pesquisa consideram que o internauta recorre a mais de um tipo de recomendação quando a seleção envolve conteúdo significativo, enquanto segue passivamente sistemas de recomendações automatizados quando o custo pessoal diretamente aplicado é baixo ou inexistente. / As the interacting select content under the influence of digital recommender systems is the research problem presented in this thesis. The abundance of data in digital repositories recovery requires effective information systems to assist the user in the management and selection of information items. Thus, the objective of this study was to investigate the behavior of the interacting in the selection of digital items across the recommendation of the Amazon’s bookshop website. The Amazon's recommendation system was investigated with the aim of understanding how the user uses an automated reference lists in the form of content recommendation. The performance of recommender systems is founded with the purpose of knowing their characteristics and functionalities. As the research problem is in your subject to the recommendation of information items, it became necessary to understand how users interact with this system to understand how the recommendations are made. The theoretical contribution of this research approaches the fields of Information and Communication. The technique applied involves qualitative research methods. By distinguishing the recommendations from reactive and mutual interactions of users, is propos in this research the Model of Recommendation Information Items consist of the following quadrants: Digital Objective Recommendations; Digital Subjective Recommendations; Analog Subjective Recommendations and Analog Objective Recommendations. To analyze the behavior of interactors in the use of these recommendations, the methodological strategy applied in-depth interviews and direct observation. The results of this research consider that the Internet uses more than one type of recommendation when the selection involves significant content, while passively follows recommendations of automated systems when applied directly to the personal cost is low or nonexistent.

Les travaux sur la gestion des services web utilisent généralement des techniques du domaine de la recherche d'information, de l'extraction de données et de l'analyse linguistique. Alternativement, nous assistons à l'émergence de la modélisation thématique probabiliste utilisée initialement pour l'extraction de thèmes d'un corpus de documents. La contribution de cette thèse se situe à la frontière de la modélisation thématique et des services web. L'objectif principal de cette thèse est d'étudier et de proposer des algorithmes probabilistes pour modéliser la structure thématique des services web. Dans un premier temps, nous considérons une approche non supervisée pour répondre à différentes tâches telles que la découverte et le regroupement de services web. Ensuite, nous combinons la modélisation thématique avec l'analyse de concepts formels pour proposer une méthode de regroupement hiérarchique de services web. Cette méthode permet une nouvelle démarche de découverte interactive basée sur des opérateurs de généralisation et spécialisation des résultats obtenus. Enfin, nous proposons une méthode semi-supervisée pour l'annotation automatique de services web. Nous avons concrétisé nos propositions par un moteur de recherche en ligne appelé WS-Portal. Nous offrons alors différentes fonctions facilitant la gestion de services web, par exemple, la découverte et le regroupement de services web, la recommandation des tags, la surveillance des services, etc. Nous intégrons aussi différents paramètres tels que la disponibilité et la réputation de services web et plus généralement la qualité de service pour améliorer leur classement (la pertinence du résultat de recherche). / The works on web services management use generally the techniques of information retrieval, data mining and the linguistic analysis. Alternately, we attend the emergence of the probabilistic topic models originally developed and utilized for topics extraction and documents modeling. The contribution of this thesis meets the topics modeling and the web services management. The principal objective of this thesis is to study and propose probabilistic algorithms to model the thematic structure of web services. First, we consider an unsupervised approach to meet different tasks such as web services clustering and discovery. Then we combine the topics modeling with the formal concept analysis to propose a novel method for web services hierarchical clustering. This method allows a novel interactive discovery approach based on the specialization and generalization operators of retrieved results. Finally, we propose a semi-supervised method for automatic web service annotation (automatic tagging). We concretized our proposals by developing an on-line web services search engine called WS-Portal where we incorporate our research works to facilitate web service discovery task. Our WS-Portal contains 7063 providers, 115 sub-classes of category and 22236 web services crawled from the Internet. In WS- Portal, several technologies, i.e., web services clustering, tags recommendation, services rating and monitoring are employed to improve the effectiveness of web services discovery. We also integrate various parameters such as availability and reputation of web services and more generally the quality of service to improve their ranking and therefore the relevance of the search result.