為了確保個人資料的隱私，本研究期望可以建構一個在主從式架構的環境中，利用語意網技術來改善現有的個人隱私偏好平臺(P3P)。透過語意網中的本體論和規則的加入希望可以提昇個人隱私偏好平臺的正規語意，來實現具有語意的個人隱私保護規範架構，確保使用者不會有解讀錯誤的情況發生，讓網站的資料使用規範，可以更符合使用者的意圖，讓原本使用者需仔細詳讀的隱私規範書，可以透過一簡單的協議過程去加以簡化閱讀隱私規範書的步驟。 / In this study I’m going to build an environment with client-server architecture and utilize Semantic Web Technology to improve the existing platform for privacy preferences (P3P) in order to ensure the privacy of personal information. With the ontology and rules of Semantic Web hopefully it will upgrade personal privacy preferences formal semantics to achieve the semantic of personal privacy protection framework to ensure that users will not misunderstand. The usage of web site information can be more in line with the user's intentions, so that the original user were required to carefully read the privacy specification can be implemented through a simple process which simplified the steps of reading privacy specification.

This thesis presents a framework for semantic Web Service discovery using descriptive (non-functional) service characteristics in a large-scale, multi-domain setting. The framework uses Web Ontology Language for Services (OWL-S) to design a template for describing non-functional service parameters in a way that facilitates service discovery, and presents a layered scheme for organizing ontologies used in service description. This service description scheme serves as a core for desigining the four main functions of a service directory: a template-based user interface, semantic query expansion algorithms, a two-level indexing scheme that combines Bloom filters with a Distributed Hash Table, and a distributed approach for storing service description. The service directory is, in turn, implemented as an extension of the Open Service Discovery Architecture. <br /><br /> The search algorithms presented in this thesis are designed to maximize precision and completeness of service discovery, while the distributed design of the directory allows individual administrative domains to retain a high degree of independence and maintain access control to information about their services.

In order to compete with the global giants, enterprises are concentrating on their core competencies and collaborating with organizations that compliment their skills and core activities. The current trend is to develop temporary alliances of independent enterprises, in which companies can come together to share skills, core competencies and resources. However, knowledge sharing and communication among multidiscipline companies is a complex and challenging problem. In a collaborative environment, the meaning of knowledge is drastically affected by the context in which it is viewed and interpreted; thus necessitating the treatment of structure as well as semantics of the data stored in enterprise repositories. Keeping the present market and technological scenario in mind, this research aims to propose tools and techniques that can enable companies to assimilate distributed information resources and achieve their business goals.

In recent years, the use of using metadata to describe and share resources has grown in importance, especially in the context of the Semantic Web.  However, access to metadata is difficult for users without experience with description logic or formal languages, and currently this description applies to most web users.  There is a strong need for interfaces that provide easy access to semantic metadata, enabling novice users to browse, query and create it easily. This thesis describes a natural language generation interface to semantic metadata called LIBER (Language Interface for Browsing and Editing Rdf), driven by domain ontologies which are integrated with domain-specific linguistic information.  LIBER uses the linguistic information to generate fluent descriptions and search terms through syntactic aggregation. The tool contains three modules to support metadata creation, querying and browsing, which implement the WYSIWYM (What You See Is What You Meant) natural language generation approach.  Users can add and remove information by editing system-generated feedback texts.  Two studies have been conducted to evaluate LIBER’s usability, and compare it to a different Semantic Web interface.  The studies showed subjects with no prior experience of the Semantic Web could use LIBER effectively to create, search and browse metadata, and were a useful source of ideas in which to improve LIBER’s usability.  However, the results of these studies were less positive than we had hoped, and users actually preferred the other Semantic Web tool.  This has raised questions about which user audience LIBER should aim for, and the extent to which the underlying ontologies influence the usability of the interface. LIBER’s portability to other domains is supported by a tool with which ontology developers without a background in linguistics can prepare their ontologies for use in LIBER by adding the necessary linguistic information.

Real-world automated reasoning systems, based on classical logic, face logically inconsistent information, and they must cope with it. It is onerous to develop such systems because classical logic is explosive. Recently, progress has been made towards semantics that deal with logical inconsistency. However, such semantics was never analyzed in the aspect of inconsistency tolerant relational model. In our research work, we use an inconsistency and incompleteness tolerant relational model called "Paraconsistent Relational Model." The paraconsistent relational model is an extension of the ordinary relational model that can store, not only positive information but also negative information. Therefore, a piece of information in the paraconsistent relational model has four truth values: true, false, both, and unknown. However, the paraconsistent relational model cannot represent disjunctive information (disjunctive tuples). We then introduce an extended paraconsistent relational model called disjunctive paraconsistent relational model. By using both the models, we handle inconsistency - similar to the notion of quasi-classic logic or four-valued logic -- in deductive databases (logic programs with no functional symbols). In addition to handling inconsistencies in extended databases, we also apply inconsistent tolerant reasoning technique in semantic web knowledge bases. Specifically, we handle inconsistency assosciated with closed predicates in semantic web. We use again the paraconsistent approach to handle inconsistency. We further extend the same idea to description logic programs (combination of semantic web and logic programs) and introduce dl-relation to represent inconsistency associated with description logic programs.

Cette thèse relève de l’ingénierie des connaissances et en particulier elle s’inscrit dans le cadre technique du web sémantique. Nous prenons un objet particulier : une théorie linguistique de la temporalité (temps et aspect), et nous proposons une traduction en plusieurs étapes de cette théorie en un artefact de représentation des connaissances : une ontologie. Nous passons en revue différents modèles (logiques, IA, linguistiques) de représentation du temps. Nous détaillons la notion d’ontologie en elle-même et telle qu’elle est utilisée dans le cadre informatique. Ensuite nous traduisons la théorie linguistique que nous choisissons en un objet vérifiant les propriétés d’un réseau d’entités qui sont caractéristiques d’une ontologie au sens du web sémantique. La dernière étape consiste en l’implémentation de notre ontologie en utilisant les standards W3C. / This is a knowledge engineering work that specifically deal with semantic web technologies. We first take an particular objet: a linguistic theory of time and aspect and we propose a translation of it into a knowledge engineering artefact (an ontology) following several steps. We look at different approach of time (logical, AI, linguistic) of time representation. Then we analyse the notion of ontology as understood in the computer science framework. An ontology is a network of entities, we give a translation of the linguistic theory of time and aspect into an ontology and we translate this resulting ontology using W3C semantic web standards.

There is an emerging demand on techniques addressing the problem of efficiently archiving and (temporal) querying different versions of evolving semantic Web data. While systems archiving and/or temporal querying are still in their early days, we consider this a good time to discuss benchmarks for evaluating storage space efficiency for archives, retrieval functionality they serve, and the performance of various retrieval operations. To this end, we provide a blueprint on benchmarking archives of semantic data by defining a concise set of operators that cover the major aspects of querying of and interacting with such archives. Next, we introduce BEAR, which instantiates this blueprint to serve a concrete set of queries on the basis of real-world evolving data. Finally, we perform an empirical evaluation of current archiving techniques that is meant to serve as a first baseline of future developments on querying archives of evolving RDF data. (authors' abstract) / Series: Working Papers on Information Systems, Information Business and Operations

[pt] Os sistemas de recomendação são um tema de pesquisa constante devido a sua grande quantidade de aplicações práticas. Estes sistemas podem ser abordados de diversas maneiras, sendo uma das mais utilizadas a filtragem colaborativa, em que para recomendar um item a um usuário são utilizados dados de comportamento de outros usuários. Porém, nem sempre os algoritmos de filtragem colaborativa atingem níveis de precisão necessários para serem utilizados em aplicações reais. Desta forma este trabalho tem como objetivo avaliar o desempenho da análise probabilística de semântica latente (PLSA) aplicado a sistemas de recomendação. Este modelo identifica grupos de usuários com comportamento semelhante através de atributos latentes, permitindo que o comportamento dos grupos seja utilizado na recomendação. Para verificar a eficácia do método, apresentamos experimentos com o PLSA utilizando os problemas de recomendação de anúncios na web e a recomendação de filmes. Evidenciamos uma melhoria de 18,7% na precisão da recomendação de anúncios na web e 3,7% de melhoria no erro quadrático sobre a Média das Médias para o corpus do Netflix. Além dos experimentos, o algoritmo foi implementado de forma flexível e reutilizável, permitindo adaptação a outros problemas com esforço reduzido. Tal implementação também foi incorporada como um módulo do LearnAds, um framework de recomendação de anúncios na web. / [en] Recommender systems are a constant research topic because of their large number of practical applications. There are many approaches to address these problems, one of the most widely used being collaborative filtering, in which in order to recommend an item to a user, data of other users` behaviors are employed. However, collaborative filtering algorithms do not always reach levels of precision required for the use in real applications. Within this context, the present work aims to evaluate the performance of the probabilistic latent semantic analysis (PLSA) applied to recommender systems. This model identifies groups of users with similar behaviors through latent attributes, allowing the use of these behaviors in the recommendation. To check the effectiveness of the method, there were presented experiments with problems of both web ad recommending and film recommending. An improvement of 18,7% were found in the accuracy of the recommendation of ads on the web and we also found 3.7% of improvement in Root Mean Square Error over the Means of Means baseline system for the Netflix corpus. Apart from the aforementioned experiments, the algorithm was implemented in a flexible and reusable way, allowing its adaptation to other problems with reduced effort. This implementation has also been incorporated as a module of LearnAds, a framework for the recommendation of ads on the web.

[pt] O consumo de conteúdo jornalístico na Web aumenta a cada dia. No entanto, boa parte desse conteúdo ainda é produzido segundo paradigmas da mídia impressa. Paralelamente a isto, a Web Semântica ou Web 3.0, adiciona uma camada de inteligência à Web, onde computadores são capazes de extrair significados dos conteúdos acessados na Web, e consequentemente, processá-los. Neste trabalho foi definido e testado um modelo de publicação de conteúdo jornalístico apoiado pela Web Semântica. Foi desenvolvida uma ferramenta de apoio para produtores de conteúdo, com o objetivo de melhorar o processo de construção de narrativas jornalísticas para web, através da sugestão de padrões narrativos e de informações objetivas que dão suporte ao tipo de narrativa desejado. Um estudo de caso foi realizado para avaliar em ambiente real o modelo proposto. Um grupo de jornalistas usou a ferramenta desenvolvida, com aceitação unânime. / [en] The use of journalistic content on the web increases every day. However, much of the content is still produced according to the paradigms of print media. Parallel to this, the Semantic Web or Web 3.0, adds a layer of intelligence to the Web, where computers are able to extract meaning from the visited web content, and consequently, process them. This work defined and tested a model of publishing news content supported by the Semantic Web. It was developed a support tool for content producers, in order to improve the process of construction of news stories for the web, using the suggestion of narrative patterns and objective information that support the desired type of narrative. A case study was conducted to evaluate the proposed model in a real environment. A group of journalists used the developed tool, with unanimous acceptance.

[pt] A Web Semântica permite a divulgação de dados na Internet através de um formato comum com o objetivo de integrar ou combinar bases de dados provenientes de diversas fontes. O Instituto Nacional de Pesquisas da Amazônia - INPA possui várias coleções de dados, principalmente científicos, que podem ser divulgadas e utilizadas na pesquisa e desenvolvimento da Amazônia e para o progresso da ciência. O objetivo deste trabalho é investigar como a utilização das tecnologias da Web Semântica, dentre elas os recursos da ferramenta Rexplorator, pode melhorar o processo de pesquisa, através do processamento da semântica, das coleções de dados biológicos do instituto. A abordagem utilizada é de desenvolver casos de uso junto com os próprios pesquisadores, através de operações simples em cima dos modelos RDFS (Resource Description Framework Schema) das próprias bases. Os casos de uso poderão ser reutilizados por outros pesquisadores, inclusive de domínios de pesquisa diferentes. Neste processo de reutilização é possível que os casos de uso sejam customizados e evoluídos colaborativamente no próprio ambiente em que foram desenvolvidos. Como resultado do processo são geradas aplicações Web que abstraem os modelos RDF (Resource Description Framework) nos quais os dados estão representados tornando possível o acesso às informações por outros pesquisadores que não conhecem esses modelos. Essa facilidade de acesso, além de permitir consultas a bases semânticas por usuários leigos em um dado domínio de pesquisa, também visa permitir que pesquisadores possam realizar consultas transdisciplinares enriquecendo sua visão no desenvolvimento da pesquisa, bem como seu poder nas tomadas de decisões políticas, econômicas e sociais, e, consequentemente, uma melhor gestão do conhecimento. / [en] The Semantic Web enables the dissemination of data on the Internet through a common format in order to integrate or combine databases from different sources. The National Institute for Amazonian Research (INPA) has several collections of data, mainly scientific, that can be disclosed and used in the research and development of the Amazon as well as for the advancement of science. The objective of this study is to investigate how the use of Semantic Web technologies, among them the tool Rexplorator, can improve the research process by processing the semantics in collections of biological data. Use cases are developed with input from INPA researchers. Queries are constructed based on RDFS (Resource Description Framework Schema) created for INPAs existing collections. Use cases can be reused by other researchers, including researchers from different fields. In this process of reuse, the customization and collaborative development of use cases is possible. The result of this process is the generation of Web applications that abstract the RDF model on which data are represented. Consequently, other researchers unfamiliar with the RDF model are also able to access information. In addition to enabling semantic queries in databases by lay users in a given field of research, this ease of access enables researchers to make transdisciplinary queries enriching their vision of research development, as well as their power in political, economic and social decision-making, and hence better knowledge management.