Knowledge base systems are brittle when the users of the knowledge base are unfamiliar with its content and structure. Querying a knowledge base requires users to state their questions in precise and complete formal representations that relate the facts in the question with relevant terms and relations in the underlying knowledge base. This requirement places a heavy burden on the users to become deeply familiar with the contents of the knowledge base and prevents novice users to effectively using the knowledge base for problem solving. As a result, the utility of knowledge base systems is often restricted to the developers themselves. The goal of this work is to help users, who may possess little domain expertise, to use unfamiliar knowledge bases for problem solving. Our thesis is that the difficulty in using unfamiliar knowledge bases can be addressed by an approach that funnels natural questions, expressed in English, into formal representations appropriate for automated reasoning. The approach uses a simplified English controlled language, a domain-neutral ontology, a set of mechanisms to handle a handful of well known question types, and a software component, called the Question Mediator, to identify relevant information in the knowledge base for problem solving. With our approach, a knowledge base user can use a variety of unfamiliar knowledge bases by posing their questions with simplified English to retrieve relevant information in the knowledge base for problem solving. We studied the thesis in the context of a system called ASKME. We evaluated ASKME on the task of answering exam questions for college level biology, chemistry, and physics. The evaluation consists of successive experiments to test if ASKME can help novice users employ unfamiliar knowledge bases for problem solving. The initial experiment measures ASKME's level of performance under ideal conditions, where the knowledge base is built and used by the same knowledge engineers. Subsequent experiments measure ASKME's level of performance under increasingly realistic conditions. In the final experiment, we measure ASKME's level of performance under conditions where the knowledge base is independently built by subject matter experts and the users of the knowledge base are a group of novices who are unfamiliar with the knowledge base. Results from the evaluation show that ASKME works well on different knowledge bases and answers a broad range of questions that were posed by novice users in a variety of domains. / text

This thesis presents the implementation of a knowledge base system for rough sets [Paw92]within the logic programming framework. The combination of rough set theory with logic programming is a novel approach. The presented implementation serves as a prototype system for the ideas presented in [VDM03a, VDM03b]. The system is available at "http://www.ida.liu.se/rkbs". The presented language for describing knowledge in the rough knowledge base caters for implicit definition of rough sets by combining different regions (e.g. upper approximation, lower approximation, boundary) of other defined rough sets. The rough knowledge base system also provides methods for querying the knowledge base and methods for computing quantitative measures. We test the implemented system on a medium sized application example to illustrate the usefulness of the system and the incorporated language. We also provide performance measurements of the system.

This dissertation focuses on Knowledge Intensive Business Services (KIBS). It aims to understand what these businesses are and to examine variety among them. In seeking to understand their diversity, I focus especially on the ‘knowledge bases’ at the core of their activities. The dissertation is based on three complementary studies. The first is a systematic review of the literature on KIBS. This is based primarily on a review of 130 carefully selected, relevant articles, and focuses on three questions: how are KIBS defined? how do KIBS compete? and how do KIBS innovate? The review shows that: (i) the literature is fragmented; most research does not build substantially on previous methods or findings; and (ii) while evidently heterogeneous, most of the literature has overlooked variety among KIBS. I also highlight what still needs to be known about KIBS.The second and third papers then focus on variety among KIBS, by classifying them according to their ‘knowledge bases’. In the first of these papers, I classify KIBS according to their primary knowledge bases, following the SAS Model, which identifies three: ‘analytical knowledge’, ‘synthetic knowledge’ and ‘symbolic knowledge’. Firms in three KIBS sectors: ‘architecture and engineering consultancy’; ‘specialist design’; and ‘computer and IT services’ are classified by their primary knowledge base according to information drawn from company websites. I then relate this classification to firm behaviour with respect to innovation, finding differences by primary knowledge base in the nature of the investments firms make to innovate, and in their propensities to innovate. In the second of the papers which relates ‘knowledge bases’ to KIBS, I develop the ‘knowledge bases’ approach conceptually, methodologically and empirically. Conceptually, I identify a hitherto unrecognised knowledge base: ‘compliance knowledge’. This relates to the knowledge of, and to interpretations of, laws and regulations. This knowledge base does not fit with any of the existing SAS types. Methodologically, I extract fuller information from company websites, and develop more sophisticated approaches to measurement, which allows multiple knowledge bases to be present in any one firm. Empirically, I successfully identify ‘compliance knowledge’, alongside ‘analytical’ and ‘symbolic knowledge’. I show that these are unevenly distributed across KIBS industries, including ‘advertising and design’, ‘architecture’, ‘engineering consultancy’ and ‘market research’, but importantly there is no one-to-one mapping between knowledge bases and industries. I discuss the implications of this, including for understanding the diversification of KIBS. This dissertation therefore contributes conceptually, methodologically and empirically to both understanding variety among KIBS and to the ‘knowledge bases’ literature.

Probabilistic data and knowledge bases are becoming increasingly important in academia and industry. They are continuously extended with new data, powered by modern information extraction tools that associate probabilities with knowledge base facts. The state of the art to store and process such data is founded on probabilistic database systems, which are widely and successfully employed. Beyond all the success stories, however, such systems still lack the fundamental machinery to convey some of the valuable knowledge hidden in them to the end user, which limits their potential applications in practice. In particular, in their classical form, such systems are typically based on strong, unrealistic limitations, such as the closed-world assumption, the closed-domain assumption, the tuple-independence assumption, and the lack of commonsense knowledge. These limitations do not only lead to unwanted consequences, but also put such systems on weak footing in important tasks, querying answering being a very central one. In this thesis, we enhance probabilistic data and knowledge bases with more realistic data models, thereby allowing for better means for querying them. Building on the long endeavor of unifying logic and probability, we develop different rigorous semantics for probabilistic data and knowledge bases, analyze their computational properties and identify sources of (in)tractability and design practical scalable query answering algorithms whenever possible. To achieve this, the current work brings together some recent paradigms from logics, probabilistic inference, and database theory.

Ma thèse a comme but l’intégration automatique de nouveaux services Web dans une base de connaissances. Pour chaque méthode d’un service Web, une vue est calculée de manière automatique. La vue est représentée comme une requête sur la base de connaissances. L’algorithme que nous avons proposé calcule également une fonction de transformation XSLT associée à la méthode qui est capable de transformer les résultats d’appel dans un fragment conforme au schéma de la base de connaissances. La nouveauté de notre approche c’est que l’alignement repose seulement sur l’alignement des instances. Il ne dépend pas des noms des concepts ni des contraintes qui sont définis par le schéma. Ceci le fait particulièrement pertinent pour les services Web qui sont publiés actuellement sur le Web, parce que ces services utilisent le protocole REST. Ce protocole ne permet pas la publication de schémas. En plus, JSON semble s’imposer comme le standard pour la représentation des résultats d’appels de services. À différence du langage XML, JSON n’utilise pas de noeuds nommés. Donc les algorithmes d’alignement traditionnels sont privés de noms de concepts sur lesquels ils se basent. / My thesis aim the automatic integration of new Web services in a knowledge base. For each method of a Web service, a view is automatically calculated. The view is represented as a query on the knowledge base. Our algorithm also calculates an XSLT transformation function associated to the method that is able to transform the call results in a fragment according to the schema of the knowledge base. The novelty of our approach is that the alignment is based only on the instances. It does not depend on the names of the concepts or constraints that are defined by the schema. This makes it particularly relevant for Web services that are currently available on the Web, because these services use the REST protocol. This protocol does not allow the publication schemes. In addition, JSON seems to establish itself as the standard for the representation of technology call results.

[pt] O problema do relacionamento de entidades refere-se à questão de explorar uma base de conhecimento, representada como um grafo RDF, para descobrir e entender como duas entidades estão conectadas. Esta questão pode ser resolvida implementando-se uma estratégia de busca de caminhos que combina uma medida de similaridade de entidades, um limite para o grau das entidades, e um limite de expansão para reduzir o espaço de busca de caminhos, e uma medida de ranqueamento de caminhos para ordenar os caminhos relevantes entre um determinado par de entidades no grafo RDF. Esta tese inicialmente apresenta um framework, chamado CoEPinKB, juntamente com uma implementação, para experimentar estratégias de busca de caminhos. O framework apresenta como pontos de flexibilização a medida de similaridade entre entidades, o limite máximo do grau das entidades, o limite de expansão, a medida de classificação de caminhos, e a base de conhecimento. Em seguida, a tese apresenta uma avaliação de desempenho de nove estratégias de busca de caminhos usando um benchmark envolvendo dois domínios de entretenimento sobre o OpenLink Virtuoso SPARQL protocol endpoint da DBpedia. Por fim, a tese apresenta o DCoEPinKB, uma versão distribuída do framework baseado em Apache Spark, que suporta a avaliação empírica de estratégias de busca de caminhos, e apresenta uma avaliação de seis estratégias de busca de caminhos em dois domínios de entretenimento sobre dados reais coletados da DBpedia. Os resultados fornecem intuições sobre o desempenho das estratégias de busca de caminhos e sugerem que a implementação do framework, instanciado com o par de medidas de melhor desempenho, pode ser usado, por exemplo, para expandir os resultados dos motores de busca em bases de conhecimento para incluir entidades relacionadas. / [en] The entity relatedness problem refers to the question of exploring a knowledge base, represented as an RDF graph, to discover and understand how two entities are connected. This question can be addressed by implementing a path search strategy that combines an entity similarity measure with an entity degree limit and an expansion limit to reduce the path search space and a path ranking measure to order the relevant paths between a given pair of entities in the RDF graph. This thesis first introduces a framework, called CoEPinKB, together with an implementation, to experiment with path search strategies. The framework features as hot spots the entity similarity measure, the entity degree limit, the expansion limit, the path ranking measure, and the knowledge base. The thesis moves on to present a performance evaluation of nine path search strategies using a benchmark from two entertainment domains over the OpenLink Virtuoso SPARQL protocol endpoint of the DBpedia. The thesis then introduces DCoEPinKB, a distributed version of the framework based on Apache Spark, that supports the empirical evaluation of path search strategies, and presents an evaluation of six path search strategies over two entertainment domains over real-data collected from DBpedia. The results provide insights about the performance of the path search strategies and suggest that the framework implementation, instantiated with the best performing pair of measures, can be used, for example, to expand the results of search engines over knowledge bases to include related entities.

La Génération Automatique de Langue Naturelle vise à produire des textes dans une langue humaine à partir d'un ensemble de données non-linguistiques. Elle comprend généralement trois sous-tâches principales: (i) sélection et organisation d'un sous-ensemble des données d'entrée; ii) détermination des mots à utiliser pour verbaliser les données d'entrée; et (iii) regroupement de ces mots en un texte en langue naturelle. La dernière sous-tâche est connue comme la tâche de Réalisation de Surface (RS). Dans ma thèse, j'étudie la tâche de RS quand les données d'entrée sont extraites de Bases de Connaissances (BC). Je présente deux nouvelles approches pour la réalisation de surface à partir de bases de connaissances: une approche supervisée et une approche faiblement supervisée. Dans l'approche supervisée, je présente une méthode basée sur des corpus pour induire une grammaire à partir d'un corpus parallèle de textes et de données. Je montre que la grammaire induite est compacte et suffisamment générale pour traiter les données de test. Dans l'approche faiblement supervisée, j'explore une méthode pour la réalisation de surface à partir de données extraites d'une BC qui ne requière pas de corpus parallèle. À la place, je construis un corpus de textes liés au domaine et l'utilise pour identifier les lexicalisations possibles des symboles de la BC et leurs modes de verbalisation. J'évalue les phrases générées et analyse les questions relatives à l'apprentissage à partir de corpus non-alignés. Dans chacune de ces approches, les méthodes proposées sont génériques et peuvent être facilement adaptées pour une entrée à partir d'autres ontologies / Natural Language Generation is the task of automatically producing natural language text to describe information present in non-linguistic data. It involves three main subtasks: (i) selecting the relevant portion of input data; (ii) determining the words that will be used to verbalise the selected data; and (iii) mapping these words into natural language text. The latter task is known as Surface Realisation (SR). In my thesis, I study the SR task in the context of input data coming from Knowledge Bases (KB). I present two novel approaches to surface realisation from knowledge bases: a supervised approach and a weakly supervised approach. In the first, supervised, approach, I present a corpus-based method for inducing a Feature Based Lexicalized Tree Adjoining Grammar from a parallel corpus of text and data. I show that the induced grammar is compact and generalises well over the test data yielding results that are close to those produced by a handcrafted symbolic approach and which outperform an alternative statistical approach. In the weakly supervised approach, I explore a method for surface realisation from KB data which does not require a parallel corpus. Instead, I build a corpus from heterogeneous sources of domain-related text and use it to identify possible lexicalisations of KB symbols and their verbalisation patterns. I evaluate the output sentences and analyse the issues relevant to learning from non-parallel corpora. In both these approaches, the proposed methods are generic and can be easily adapted for input from other ontologies for which a parallel/non-parallel corpora exists

Introdução: A Medicina Baseada em Evidências, apesar da grande profusão de publicações da área, enfrenta desafios no intuito de melhorar a qualidade da assistência à saúde. O conhecimento gerado por suas publicações demora a ser posta em prática. Os softwares CDSS de apoio à decisão clínica, podem ser a solução de incorporação das evidências na prática clínica. Esses sistemas já foram associados a melhorias na qualidade de diversos aspectos da assistência à saúde, como a organização, minimização de erros, redução de custos, aumento da eficiência dos cuidados, mas pesquisas com desfechos centrados no paciente ainda são raras. Como outra qualquer intervenção em saúde, as afirmações de que os CDSS são benéficos para o paciente necessitam de confirmação por ensaios clínicos. Objetivos: Verificar se o uso dos CDSS com base em evidências, está associado com melhores resultados clínicos orientados para o paciente. Métodos: Revisão sistemática da literatura dos ensaios clínicos controlados e randomizados que compararam diretamente o uso de CDSS com práticas clínicas convencionais considerando os desfechos clínicos classificados como orientados para o paciente. Resultados: Nossa estratégia de pesquisa identificou 51283 artigos na base MEDLINE-PubMed, sendo 311 selecionados para leitura de título e resumo após a aplicação do filtro para ensaio clínico randomizado, 45 selecionados para leitura do texto completo, dos quais 19 preencheram o critério de elegibilidade. Outros 9 ensaios foram incluídos através da realização de um overview das revisões sistemáticas anteriores. Os ensaios foram publicados entre os anos de 1995 e 2015 e realizados em cinco contextos assistenciais, com duração máxima de 12 meses. A maioria das fontes de evidências que alimentaram os sistemas foram diretrizes de órgão governamental ou sociedades de especialidades. Doze ensaios avaliaram mortalidade, 14 avaliaram hospitalizações ou atendimento de emergência e 6 avaliaram desfechos relacionados a presença de sintomas. Foram realizadas meta-análises de acordo com o contexto assistencial e o tipo de desfecho. Somente uma meta-análise envolvendo a mortalidade de pacientes tratados em ambulatório por diferentes condições clínicas se mostrou estatisticamente significante, favorável ao grupo CDSS, em 3 ensaios randomizados por aglomerado, com risco de viés considerado moderado, que compromete a qualidade da evidência. Conclusões Apesar do potencial dos CDSS no apoio de intervenções de saúde, não há evidência de boa qualidade de que sejam efetivos para aumentar a sobrevida ou a qualidade de vida dos pacientes. O número de ensaios que avaliam esses desfechos, os períodos de tempo pelos quais os pacientes foram seguidos, o número insuficiente de participantes, bem como a heterogeneidade entre os estudos analisados quanto aos cenários clínicos e as fontes de informação que alimentam os softwares não permitiram resultados mais conclusivos / Background: In spite of the wealth of publications in the field, Evidence-Based Medicine faces challenges in order to improve quality of health care. It takes too long for knowledge produced by its publications to be put into practice. Clinical Decision Support Systems (CDSS) may be a solution for incorporation of evidence into clinical practice. These systems have been associated with improvements in quality of various aspects of health care, including its organization, error minimizations, cost reductions and increases in its efficiency, but patient-oriented outcomes are still rare in research literature. Like any other healthcare intervention, claims that CDSS are beneficial for patients need to be confirmed by clinical trials. Objective: To verify whether the use of evidence-based Clinical Decision Support Systems is associated with improved patient-oriented clinical outcomes. Methods: Systematic literature review of randomized controlled trials that directly compared the use of CDSS with usual practice considering clinical outcomes classified as patient-oriented. Results: Our search strategy has identified 51,283 entries in MEDLINE-PubMed and, after filtering for randomized controlled trials 311 papers were selected for title and abstract reading. Forty-five were selected for full-text reading of which 19 have met eligibility criteria. Another nine trials were included after an overview of previous systematic reviews. Trials were published between 1995 and 2015 and performed in five care settings with a maximum follow-up of 12 months. Most evidence sources feeding systems´ knowledge bases were government agency guidelines or specialty societies. Twelve trials have assessed mortality, 14 have assessed hospital admissions and/or emergency visits and nine have assessed symptom-related outcomes. Meta-analyses were performed according to trials´ care setting and outcome types. Only a meta-analysis of three cluster-randomized trials involving mortality among outpatients with different clinical conditions was statistically significant, favouring CDSS group, but risk of bias was moderate, compromising the quality of evidence. Conclusions: Despite the potential of CDSS to improve healthcare quality there is no reliable evidence that they improve patients´ life extension or quality. The insufficient numbers of trials assessing these outcomes, studies´ subjects and follow-up periods, the heterogeneities of clinical settings across studies and knowledge bases feeding the systems impede achieving results that are more conclusive

Apesar de sua inerente indecidibilidade e do problema da negação, extensões da lógica de primeira ordem tem se mostrado capazes de superar a questão da monotonicidade, vindo a constituir esquemas de representação de conhecimento de expressividade virtualmente universal. Resta entretanto solucionar ou pelo menos amenizar as conseqüências do problema do controle, que limitam o seu emprego a aplicações de pequeno a médio porte. Investigações nesse sentido [BOW 85] [MON 88] indicam que a chave para superar a explosão inferencial passa obrigatoriamente pela estruturação do conhecimento, de modo a permitir o exercício de algum controle sobre as possíveis derivações dele decorrentes. O modelo das hiperredes [GEO 85] parece atingir tal objetivo, dado o seu elevado potencial de estruturação e o instrumental que oferece para o tratamento de construções descritivas, operacionais e organizacionais. Além disso, a simplicidade e uniformidade sintática de suas entidades primitivas possibilita uma interpretação semântica bastante clara do modelo original, por exemplo, baseada em grafos. O presente trabalho representa uma tentativa de associar a programação em lógica ao formalismo das hiperredes, visando obter um novo modelo capaz de preservar as expressividade da primeira, beneficiando-se simultaneamente do potencial heurístico e estrutura do segundo. Inicialmente procura-se obter uma noção clara da natureza do conhecimento e de seus mecanismos com o objetivo de caracterizar o problema da representação de conhecimento. Diferentes esquemas correntemente empregados para esse fim (sistemas de produções, redes semânticas, sistemas de frames, programação em lógica e a linguagem Krypton) são estudados e caracterizados do ponto de vista de sua expressividade, potencial heurístico e conveniência notacional. A programação em lógica é objeto de um estudo em maior profundidade, sob os enfoques modelo-teorético e prova-teorético. Sistemas de programação em lógica - particularmente a linguagem Prolog e extensões em nível meta - são investigados como esquemas de representação de conhecimento, considerando seus aspectos sintáticos e semânticos e a sua retação com Sistemas Gerenciadores de Bases de Dados. O modelo das hiperredes é apresentado introduzindo-se, entre outros, os conceitos de hipernodo, hiperrelação e protótipo, assim como as propriedades particutares de tais entidades. A linguagem Hyper, para o tratamento de hiperredes, é formalmente especificada. Emprega-se a linguagem Prolog como formalismo para a representação de Bases de Conhecimento estruturadas segundo o modelo das hiperredes. Sob tal abordagem uma Base de Conhecimento é vista como um conjunto (possivelmente vazio) de objetos estruturados ou peças de conhecimento, que por sua vez são classificados como hipernodos, hiperrelações ou protótipos. Um mecanismo top-down para a produção de inferências em hiperredes é proposto, introduzindo-se os conceitos de aspecto e visão sobre hiperredes, os quais são tomados como objetos de primeira classe, no sentido de poderem ser valores atribuídos a variáveis. Estuda-se os requisitos que um Sistema Gerenciador de Bases de Conhecimento deve apresentar, do ponto de vista da aplicação, da engenharia de conhecimento e da implementação, para suportar efetivamente os conceitos e abstrações (classificação, generalização, associação e agregação) associadas ao modelo proposto. Com base nas conclusões assim obtidas, um Sistema Gerenciador de Bases de Conhecimento (denominado Rhesus em alusão à sua finalidade experimental é proposto e especificado, objetivando confirmar a viabilidade técnica do desenvolvimento de aplicações baseadas em lógica e hiperredes. / In spite of its inherent undecidability and the negation problem, extensions of first-order logic have been shown to be able to overcome the question of the monotonicity, establishing knowledge representation schemata with virtuatLy universal expressiviness. However, one still has to solve, or at Least to reduce the consequences of the control problem, which constrains the use of Logic-based systems to either small or medium-sized applications. Investigations in this direction [BOW 85] [MON 88] indicate that the key to overcome the inferential explosion resides in the proper knowledge structure representation, in order to have some control over possible derivations. The Hypernets Model [GEO 85] seems to reach such goat, considering its high structural power and the features that it offers to deal with descriptive, operational and organizational knowledge. Besides, the simplicity and syntactical uniformity of its primitive notions allows a very clear definition for its semantics, based, for instance, on graphs. This work is an attempt to associate logic programming with the hypernets formalism, in order to get a new model, preserving the expressiveness of the former and the heuristic and structural power of the latter. First we try to get a clear notion of the nature of knowledge and its main aspects, intending to characterize the knowledge representation problem. Some knowledge representation schemata (production systems, semantic networks, frame systems, Logic programming and the Krypton Language) are studied and characterized from the point of view of their expressiveness, heuristic power and notational convenience. Logic programming is the subject of a deeper study, under the model-theoretic and proof-theoretic approaches. Logic programming systems - in particular the Prolog Language and metateuel extensions- - are investigated as knowledge representation schemata, considering its syntactic and semantic aspects and its relations with Data Base Management Systems. The hypernets model is presented, introducing the concepts of hypernode, hyperrelation and prototype, as well as the particular properties of those entities. The Hyper language, for the handling of h y pernets, is formally specified. Prolog is used as a formalism for the representation of Knowledge Bases which are structured as hypernets. Under this approach a Knowledge Brie is seen rrG a (possibly empty) set of structured objects, which are classified as hypernodes, hyperreLations or prototypes. A mechanism for top-down reasoning on hypernets is proposed, introducing the concepts of aspect and vision, which are taken as first-class objects in the sense that they could be (-Ysigned as values to variables. We study the requirements for the construction of a Knowledge Base Management System from the point of view of the user's need-1', knowledge engineering support and implementation issues, actually supporting the concepts and abstractions (classification, generalization, association and aggregation) rYsociated with the proposed model. Based on the conclusions of this study, a Knowledge Base Management System (called Rhesus, refering to its experimental objectives) is proposed, intending to confirm the technical viability of the development of applications based on logic and hypernets.

Apesar de sua inerente indecidibilidade e do problema da negação, extensões da lógica de primeira ordem tem se mostrado capazes de superar a questão da monotonicidade, vindo a constituir esquemas de representação de conhecimento de expressividade virtualmente universal. Resta entretanto solucionar ou pelo menos amenizar as conseqüências do problema do controle, que limitam o seu emprego a aplicações de pequeno a médio porte. Investigações nesse sentido [BOW 85] [MON 88] indicam que a chave para superar a explosão inferencial passa obrigatoriamente pela estruturação do conhecimento, de modo a permitir o exercício de algum controle sobre as possíveis derivações dele decorrentes. O modelo das hiperredes [GEO 85] parece atingir tal objetivo, dado o seu elevado potencial de estruturação e o instrumental que oferece para o tratamento de construções descritivas, operacionais e organizacionais. Além disso, a simplicidade e uniformidade sintática de suas entidades primitivas possibilita uma interpretação semântica bastante clara do modelo original, por exemplo, baseada em grafos. O presente trabalho representa uma tentativa de associar a programação em lógica ao formalismo das hiperredes, visando obter um novo modelo capaz de preservar as expressividade da primeira, beneficiando-se simultaneamente do potencial heurístico e estrutura do segundo. Inicialmente procura-se obter uma noção clara da natureza do conhecimento e de seus mecanismos com o objetivo de caracterizar o problema da representação de conhecimento. Diferentes esquemas correntemente empregados para esse fim (sistemas de produções, redes semânticas, sistemas de frames, programação em lógica e a linguagem Krypton) são estudados e caracterizados do ponto de vista de sua expressividade, potencial heurístico e conveniência notacional. A programação em lógica é objeto de um estudo em maior profundidade, sob os enfoques modelo-teorético e prova-teorético. Sistemas de programação em lógica - particularmente a linguagem Prolog e extensões em nível meta - são investigados como esquemas de representação de conhecimento, considerando seus aspectos sintáticos e semânticos e a sua retação com Sistemas Gerenciadores de Bases de Dados. O modelo das hiperredes é apresentado introduzindo-se, entre outros, os conceitos de hipernodo, hiperrelação e protótipo, assim como as propriedades particutares de tais entidades. A linguagem Hyper, para o tratamento de hiperredes, é formalmente especificada. Emprega-se a linguagem Prolog como formalismo para a representação de Bases de Conhecimento estruturadas segundo o modelo das hiperredes. Sob tal abordagem uma Base de Conhecimento é vista como um conjunto (possivelmente vazio) de objetos estruturados ou peças de conhecimento, que por sua vez são classificados como hipernodos, hiperrelações ou protótipos. Um mecanismo top-down para a produção de inferências em hiperredes é proposto, introduzindo-se os conceitos de aspecto e visão sobre hiperredes, os quais são tomados como objetos de primeira classe, no sentido de poderem ser valores atribuídos a variáveis. Estuda-se os requisitos que um Sistema Gerenciador de Bases de Conhecimento deve apresentar, do ponto de vista da aplicação, da engenharia de conhecimento e da implementação, para suportar efetivamente os conceitos e abstrações (classificação, generalização, associação e agregação) associadas ao modelo proposto. Com base nas conclusões assim obtidas, um Sistema Gerenciador de Bases de Conhecimento (denominado Rhesus em alusão à sua finalidade experimental é proposto e especificado, objetivando confirmar a viabilidade técnica do desenvolvimento de aplicações baseadas em lógica e hiperredes. / In spite of its inherent undecidability and the negation problem, extensions of first-order logic have been shown to be able to overcome the question of the monotonicity, establishing knowledge representation schemata with virtuatLy universal expressiviness. However, one still has to solve, or at Least to reduce the consequences of the control problem, which constrains the use of Logic-based systems to either small or medium-sized applications. Investigations in this direction [BOW 85] [MON 88] indicate that the key to overcome the inferential explosion resides in the proper knowledge structure representation, in order to have some control over possible derivations. The Hypernets Model [GEO 85] seems to reach such goat, considering its high structural power and the features that it offers to deal with descriptive, operational and organizational knowledge. Besides, the simplicity and syntactical uniformity of its primitive notions allows a very clear definition for its semantics, based, for instance, on graphs. This work is an attempt to associate logic programming with the hypernets formalism, in order to get a new model, preserving the expressiveness of the former and the heuristic and structural power of the latter. First we try to get a clear notion of the nature of knowledge and its main aspects, intending to characterize the knowledge representation problem. Some knowledge representation schemata (production systems, semantic networks, frame systems, Logic programming and the Krypton Language) are studied and characterized from the point of view of their expressiveness, heuristic power and notational convenience. Logic programming is the subject of a deeper study, under the model-theoretic and proof-theoretic approaches. Logic programming systems - in particular the Prolog Language and metateuel extensions- - are investigated as knowledge representation schemata, considering its syntactic and semantic aspects and its relations with Data Base Management Systems. The hypernets model is presented, introducing the concepts of hypernode, hyperrelation and prototype, as well as the particular properties of those entities. The Hyper language, for the handling of h y pernets, is formally specified. Prolog is used as a formalism for the representation of Knowledge Bases which are structured as hypernets. Under this approach a Knowledge Brie is seen rrG a (possibly empty) set of structured objects, which are classified as hypernodes, hyperreLations or prototypes. A mechanism for top-down reasoning on hypernets is proposed, introducing the concepts of aspect and vision, which are taken as first-class objects in the sense that they could be (-Ysigned as values to variables. We study the requirements for the construction of a Knowledge Base Management System from the point of view of the user's need-1', knowledge engineering support and implementation issues, actually supporting the concepts and abstractions (classification, generalization, association and aggregation) rYsociated with the proposed model. Based on the conclusions of this study, a Knowledge Base Management System (called Rhesus, refering to its experimental objectives) is proposed, intending to confirm the technical viability of the development of applications based on logic and hypernets.