Esta pesquisa corresponde ao estudo de técnicas de hipermídia adaptativa (HA), visando melhorias nos meios para organização e disponibilização de conteúdo jornalístico online de acordo com o comportamento e interesse individual de um usuário em busca de notícias e informação. Do ponto de vista do design, a abordagem sobre o assunto corresponde, basicamente, à busca por métodos inteligentes de alimentação de uma interface gráfica com conteúdo noticioso, baseando-se em estudos do comportamento de navegação do usuário. A idéia é que as estatísticas matemáticas deste comportamento sejam traduzidas na exibição do conteúdo para atender de forma antecipada possíveis interesses do usuário. Concentrou-se como área de interesse focal, as matérias que serão incluídas na página principal e a forma de como serão distribuídas. Para isto foram criados alguns modelos de layout para a página principal. Estes modelos de layout possuem slots (espaços) onde as notícias são inseridas. Estes slots, por sua vez, estão distribuídos hierarquicamente de tal forma que os considerados mais importantes são aqueles com fotos e localizados nas melhores posições da página. A metodologia aqui criada foi aplicada como estudo na página principal do portal www.globo.com de conteúdo predominantemente noticioso e pertencente a um dos principais grupos de empresas de comunicação do Brasil. / This research concerns a methodology to organize the homepage of online news in order to adapt it according to the main interests of the users. The designers approach to this issue involves the usage of inteligent procedures based on the navigational behavior of the user and statistical analysis of such behaviour. Our main interest concerns the selection of the news to be inserted into this home page and how to distribute them. We deal with some templates for such first page. These templates have slots where news is inserted. These slots are hierarchically distributed in such a way that most important slots are those with photos and larger texts and are located in the best positions. These best slots are filled out with the most interesting news according to each users interests. This whole methodology has been applied to the journalistic site www.globo.com which belongs to a major Brazilian communication company.

A maior parte da população mundial se comunica de forma multimodal (fala, gestos, expressões faciais, etc.). Na medida em que algum destes modos falta, a pessoa afetada encontra dificuldades para manifestar suas idéias e pensamentos. Este trabalho é destinado a pessoas com dificuldades severas de fala e graves danos, tamb6m, na parte motora, o que as impede de se comunicarem por outras formas usuais, como a linguagem de sinais dos surdos, por exemplo, restando-lhes buscar alternativas de comunicação. Estas alternativas são pesquisadas em uma área denominada Comunicação Alternativa e Aumentativa (comumente chamada de AAC, do inglês: Augmentative and Alternative Communication), dentro da qual ha uma linha que estuda a utilização de sistemas simbólicos para comunicação, que é abordada neste trabalho. A fim de auxiliar estas pessoas que apresentam distúrbios motores e de fala, na sua busca por autonomia pessoal, estudou-se maneiras de facilitar a utilização destes sistemas simbólicos de comunicação, com o emprego de recursos de Multimídia e técnicas de Inteligência Artificial. O intuito foi o de auxiliá-las no aprendizado da forma de comunicação a ser utilizada e de proporcionar-lhes uma interação mais amigável e eficaz com o sistema. Para estes fins, foram estudados os conceitos básicos de Comunicação Alternativa e Aumentativa, bem como diversas técnicas de Inteligência Artificial (Modelagem de Usuário, Interfaces Inteligentes, Ajudas Inteligentes, etc.), a fim de verificar quais se adequavam mais aos propósitos do trabalho. Como resultado destes estudos, foi proposto um modelo de sistema inteligente que objetiva empregar estas técnicas e conceitos abordados. Este modelo tem como objetivo aprimorar os sistemas de AAC existentes, principalmente, nos seguintes aspectos: adaptação as preferências do usuário (como sua velocidade de varredura, símbolos mais utilizados) e seu nível de conhecimento do sistema simbólico em questão e do próprio sistema computadorizado que esta sendo utilizado; prestação de auxilio individualizado no aprendizado dos símbolos utilizados, através do acesso ao significado viso-auditivo real ou aproximado dos mesmos, possibilitando o use de tabuleiros de comunicação "normais" (não computadorizados) de forma mais eficaz. A partir deste modelo, foi construído um protótipo, denominado FALAS (Ferramenta Alternativa de Aquisição Simbólica), com o intuito de validar as idéias do trabalho. Além dos objetivos principais do modelo, o protótipo pode ser utilizado, não só pelo usuário padrão AAC, mas também pelas pessoas que irão comunicar-se com ele e ajudá-lo na interação com os símbolos. Por fim, levantou-se uma serie de sugestões, as quais utilizando as pesquisas realizadas para este trabalho, poderiam auxiliar na construção de sistemas para outras áreas, em especial para a Reabilitação, onde a redução de esforços por pane do usuário e sua maior compreensão do que esta se passando, lhes proporciona uma maior autonomia, o que a maioria dos estudos, nesta linha, buscam. Alem disto, foram sugeridas varias idéias a fim de dar seguimento a este trabalho e incentivar pesquisas nesta linha. / Most of the population of the world use to communicate in a multimodal way (by using speech, gestures, facial expression, etc.). If there is a lack of any of these abilities, this person will have difficulties to express his ideas or thoughts. This work is directed to people with major speech difficulties and severe motor impairments. These difficulties prevent them to communicate by the usual means, as the signal language for deafs, for example, so they need to use alternative means of communication. These alternative means of communication are studied in an area called Augmentative and Alternative Communication (AAC). In this area there is an approach which studies the usage of symbolic systems to communicate, and it will be addressed in this work. In order to help this kind of people in his search for personnal autonomy, we studied some ways to make the symbolic systems easier for them to use, by applyind Multimedia and Artificial Intelligence techniques. The goal was to help them to learn how to use this new mean of communication and to provide a more friendly and efficient interaction with the system. Finally, we are suggesting many aspects that can direct the designs and implementation of systems to other areas, namely the Rehabilitation, where a reduction in the effort needed from the users and their better understanding this activities result in a greater autonomy. This greater autonomy is searched by most of the works in this area. Besides, many ideas are suggested in order to continue this work and to help the research in this area.

Esta pesquisa corresponde ao estudo de técnicas de hipermídia adaptativa (HA), visando melhorias nos meios para organização e disponibilização de conteúdo jornalístico online de acordo com o comportamento e interesse individual de um usuário em busca de notícias e informação. Do ponto de vista do design, a abordagem sobre o assunto corresponde, basicamente, à busca por métodos inteligentes de alimentação de uma interface gráfica com conteúdo noticioso, baseando-se em estudos do comportamento de navegação do usuário. A idéia é que as estatísticas matemáticas deste comportamento sejam traduzidas na exibição do conteúdo para atender de forma antecipada possíveis interesses do usuário. Concentrou-se como área de interesse focal, as matérias que serão incluídas na página principal e a forma de como serão distribuídas. Para isto foram criados alguns modelos de layout para a página principal. Estes modelos de layout possuem slots (espaços) onde as notícias são inseridas. Estes slots, por sua vez, estão distribuídos hierarquicamente de tal forma que os considerados mais importantes são aqueles com fotos e localizados nas melhores posições da página. A metodologia aqui criada foi aplicada como estudo na página principal do portal www.globo.com de conteúdo predominantemente noticioso e pertencente a um dos principais grupos de empresas de comunicação do Brasil. / This research concerns a methodology to organize the homepage of online news in order to adapt it according to the main interests of the users. The designers approach to this issue involves the usage of inteligent procedures based on the navigational behavior of the user and statistical analysis of such behaviour. Our main interest concerns the selection of the news to be inserted into this home page and how to distribute them. We deal with some templates for such first page. These templates have slots where news is inserted. These slots are hierarchically distributed in such a way that most important slots are those with photos and larger texts and are located in the best positions. These best slots are filled out with the most interesting news according to each users interests. This whole methodology has been applied to the journalistic site www.globo.com which belongs to a major Brazilian communication company.

As pessoas têm acesso a uma vasta gama de informações devido a grande oferta e aos recursos da Internet, porém despendem muito tempo na busca do que realmente é interessante ou útil para elas. A dificuldade de encontrar a informação correta é aumentada quando a informação disputa a atenção de uma pessoa com uma série de outras informações não tão relevantes. Procurando minimizar esta dificuldade e auxiliar no acesso a informação interessante, são aplicados desde sistemas de recuperação de informação até sistemas de filtragem de informação. Os sistemas de recuperação são amplamente difundidos na Internet através dos motores de busca (por exemplo, google.com, av.com, citeseer.ist.psu.edu), porém um problema neste tipo de aplicação constitui-se na necessidade do usuário apresentar os termos (palavras-chave) que são relevantes para a consulta. filtragem de informação, tendo como representante os Sistemas de Recomendação, surge como uma nova abordagem que procura liberar o usuário da exigência de criar consultas com palavras-chave, ou seja, a filtragem baseada em conteúdo procura casar o perfil do usuário e o conteúdo dos itens a serem recomendados, e então, oferecer alguns destes itens aos usuários. Por fim, surgiram sistemas que não se baseavam na análise do conteúdo dos itens, mas sim na reputação de um item junto aos outros usuários, ou seja, o usuário recebe a recomendação de um item que pode ser do seu interesse frente à colaboração de outros usuários que avaliaram o item. A questão maior nesta abordagem está no quanto a opinião de um usuário que avaliou um item é relevante para servir como colaboração na elaboração da recomendação para outro usuário. Esta tese constitui-se em uma proposta para modelar e incluir a relevância da opinião do usuário no processo de recomendação colaborativa, ou seja, apresenta uma abordagem de Sistemas de Recomendação para recomendar itens baseando-se em informação adicional − definida como relevância da opinião do usuário − além das típicas informações utilizadas na grande maioria dos Sistemas de Recomendação. Esta inclusão da relevância da opinião constitui-se em uma alternativa para que o usuário alvo da recomendação consiga identificar qual a importância de um determinado item recomendado frente à relevância de opinião dos recomendadores. A idéia apresentada é a de que pessoas com maior relevância de opinião poderiam melhor avaliar e recomendar itens. / Nowadays, people have access to a huge amount of information due to the Internet's resources. However they spend too much time searching for interesting, adequate or useful information. The difficulty to find worthwhile information increases when interesting things dispute the user's attention. Information retrieval and information filtering systems are applicable in order to minimize search difficulties, aiming to aid the user in the search for worthwhile information. Information retrieval systems are widely spread in the Internet through search engines (e.g., google.com, av.com, citeseer.ist.psu.edu). However there is a problem in this kind of application, which consists in compelling the user to know the terms (keywords) that are relevant for the search. Recommender Systems are an information filtering solution. They present a different approach that frees the user from creating queries with keywords. It means that the system tries to match the user's profile (historical interests) with the content of items to be recommended, and then offers these items to the user (recommendee). In parallel, an alternative approach to item recommendation was proposed, this one based on the offering of items based on other users’ opinion, i.e. the user receives an item recommendation based on the evaluation of other users (collaborative filtering or social filtering). However, a different question is raised here − how much the opinion of a user who evaluated an item is relevant to be employed in the recommendation process applying a collaborative method? This thesis presents a new approach to model and include in the collaborative recommendation process additional information named Recommender's Rank, which represents the relevance of the user's opinion and complements the typical information used in the large majority of Recommender Systems. This approach is an alternative to aid the user to identify the importance of a recommended item based on other users' opinions, as people with higher relevance of opinion are more likely to better evaluate and recommend items.

Made available in DSpace on 2016-08-17T14:52:49Z (GMT). No. of bitstreams: 1 Ismenia Ribeiro de Oliveira.pdf: 2858888 bytes, checksum: 1f919da635a28d5ee15d5832df5d95b1 (MD5) Previous issue date: 2004-02-10 / This work proposes an agent-based pattern system for design of adaptive multi-agent systems using user-modeling techniques. The pattern system is composed of a conceptual, an architectural, and design patterns. The patterns describe recurrent problems and design solutions for user modeling and development of adaptive multi-agent systems. The pattern mining is based on the analysis of: concepts and techniques for development of adaptive and adaptable systems; user modeling techniques; and multi-agent design techniques. An initial validation of the pattern system has been conducted through the development of a case study on the domain of information access, where patterns in the system have been reused on the development of a multi-agent system for personalized information access. / Este trabalho propõe um sistema de padrões baseados em agentes para o projeto de sistemas multiagente adaptativos e adaptáveis que utilizam técnicas de modelagem de usuários. O sistema de padrões é composto por um padrão conceitual, um padrão arquitetural e cinco padrões de projeto. Os problemas, as soluções e os conceitos, comuns no projeto da modelagem de usuários, de sistemas adaptativos e no desenvolvimento de agentes de software, são analisados e descritos na forma de padrões. A metodologia para a extração dos padrões é baseada na análise dos conceitos e técnicas para o desenvolvimento de sistemas adaptativos e adaptáveis, das técnicas de modelagem de usuário e dos conceitos e técnicas para o projeto de sistemas multiagente e agentes de software. Uma avaliação preliminar, do sistema de padrões proposto, é feita por meio de um estudo de caso no domínio do acesso à informação. O estudo consiste em identificar e analisar a reutilização do sistema de padrões no desenvolvimento de aplicações multiagente para o acesso à informação personalizada.

Les travaux de recherche de cette thèse portent sur l'amélioration des capacités sociales d'un système conversationnel en interaction avec un humain. Lorsque le système n'est pas dédié à une tâche particulière, il doit tenir compte de difficultés relevant de l'interaction sociale elle-même. L'humour est un mécanisme naturel dans les interactions sociales. Nous considérons un humour-machine comme une simulation de comportements simplifiés des capacités humoristiques humaines: dérision, blagues, jeux de mots. Les travaux de cette thèse s'appuient sur des théories issues de domaines variés en sociologie, psychologie, neurosciences et linguistique pour l'intégration de cet humour-machine dans un système robotique. Implémentées dans certains systèmes de dialogue, ces capacités humoristiques sont cependant rarement utilisées pour pouvoir choisir les comportements à générer du robot. Dans nos travaux, la mise en œuvre des comportements humoristiques du système en conversation est réalisée en utilisant la théorie des rites d'interaction. L'estimation de la face de l'interlocuteur permet de diriger le comportement du robot dans la conversation casuelle humoristique. Les facteurs expressifs d'une perte ou d'une valorisation de la face sont liés à des états mentaux exprimés dans une situation donnée. Pour réaliser cette estimation de la face, nous étudions, à partir de corpus créés à cet effet, les réactions comportementales, affectives et expressives des participants à différents types d'humour réalisés par le robot et ayant des impacts variables sur celle-ci (l'humour prenant pour cible le robot, le participant ou un autre sujet). Les réactions des participants à l'humour sont établies sur une représentation multi-niveaux d'indices émotionnels, comportementaux et linguistiques, extraits à partir de l'audio.Des règles sont ainsi construites à partir de l'apprentissage automatique de ces indices issus des corpus, concernant l'appréciation de la réaction des participants à l'humour et la mise à jour de l'estimation de la face présentée du participant. Leur implémentation dans un système automatique nous permet de les évaluer. De nombreuses expérimentations ont été menées avec des publics variés : personnes âgées, adultes, adolescents. Enfin, l'utilisation des préférences du participant à l'humour dans la conversation fait émerger des questions éthiques, notamment face au pouvoir persuasif et manipulateur de l'humour. / This doctoral dissertation is about the improvement of social capacities of a conversationnal system to interact with humans. When the system is not dedicated to one particular task, it must take into account the inherent difficulties of social interaction it-self. Humor is a natural mechanism present in social interactions. We consider humour in a robotic system as a simulation of simplified behaviors from human humor : derision, jokes, puns. This work is based on theories issued from various research domains as sociology, psychology, neurosciences and linguistics to enable integration of humor in a robotic system. Implemented in some dialog systems, humorous capacities are however rarely used when programming the robot’s behavior. In our study, the humourous behavior is implemented in the system by using the ritual theory of face-work. The face analysis of the interlocutor can be used to direct the robot’s reactions during a casual humorous talk. In order to evaluate the faces of participants in interaction, we study, using data collections created for this purpose, the participant’s behavior, emotionnal and expressive responses to different types of humor (humorous act targeting the robot, the participant or a neutral subject). Participant's reaction to humor are made upon a multi-level processing of emotionnal, linguistic and behavioral cues.Machine learning is used to extract rules defining appreciation or not and update the participant's face evaluation in regards of the humorous act produced by the robot. An implementation of these rules in an automatic dialog system allows us to evaluate their accuracy. Numerous experiments were carried out on various populations : elderly persons, adults, teenagers. Finally, the use of the participant’s preferences in the conversation raises ethical questions, in particular against the persuasive and manipulative power of humor.

(in English): Conceptual graphs are a formal knowledge representation language introduced by John F. Sowa, an American specialist on Artificial Intelligence, at the end of the seventies. They are the synthesis of heuristic and formalistic approach to Artificial Intelligence and knowledge procession. They provide meaning and knowledge in form, which is logically precise, human- readable and untestable, and it is applicable in the computing domain in general. Conceptual graphs can be expressed through a first-order logic, which makes them a quality tool for intelligent reasoning. Their notation CGIF was standardised by norm ISO/IEC 24707:2007 as one of the three dialects of Common logic, which frames the set of logic based on logic. Conceptual graphs are also mappable to knowledge representation languages standardised for the Semantic Web; OWL and RDF (S). This work introduces the conceptual graph theory in the context of scientific fields like linguistics, logic and artificial intelligence. It represents the formalism proposed by John F. Sowa and some extensions that have emerged over the past decades, along with the need for improvements to the representational properties of graphs. Finally, the work provides an illustrative overview of the implementation and use of conceptual graphs in practice....

Cette thèse consiste à explorer l’usage de la réalité augmenté sonore pour la visite de musées. Notre objectif est de proposer un audioguide permettant d’immerger le visiteur dans une scène sonore constituée de sons ambiants et de commentaires associés aux objets exposés, et de minimiser ses efforts pour découvrir ces objets et interagir avec cet environnement sonore. La première contribution de cette thèse concerne la mise en place d’une preuve de concept de SARIM (Sound Augmented Reality Interface for visiting Museum). Cette preuvede concept a été développée en utilisant des capteurs de position et d’orientation filaire et non filaire. La deuxième contribution concerne la modélisation de la visite augmentée par la dimension sonore. Après une étude des modèles existants, l’objectif est de concevoir un modèle comprenant une représentation du visiteur,du paysage sonore et de la navigation et offrant une grande flexibilité pour créer l’environnement sonore. Ce modèle a comme finalité de faciliter la conception de différents types de scénarios de visite sur la base de la notion de zone d’audibilité. La troisième contribution de cette thèse est le travail d’évaluation mené dans un environnement réel qu’est le musée des arts et métiers de Paris, et qui a permis de confirmer l’utilisabilité, ainsi que l’apport didactique et ludique que procure la réalité augmentée sonore en général et le système SARIM en particulier pour prolonger et enrichir la visite de musées. / The goal of this thesis is to explore the use of sound to enhance the museum visit. We aim to provide anaudioguide to immerse the visitor in a soundstage consisting of ambient sounds and comments associated withthe exhibits, and minimize its efforts to discover these objects and interact with the sound environment. Thefirst contribution of this thesis is the implementation of a proof of concept of SARIM (Sound AugmentedReality Interface for visiting Museum). This proof of concept was developed using position sensors andguidance wired and wirelessly. The second contribution concerns the modeling of the augmented visit by thesound dimension. After a review of existing models, the objective is to design a model that includes arepresentation of the visitor, the soundscape and navigation, offering the flexibility to create the soundenvironment. This model has the purpose of facilitating the design of different types of scenarios based on theconcept of audibility area. The Third contribution of this thesis is the evaluation conducted in a realenvironment what the Museum of Arts and Crafts in Paris, which confirmed the usability, as well as providingeducational and ludic impact of the audio augmented reality in general and the SARIM in particular to extendand enrich the museum visits.

User Modeling and Machine Learning for User Modeling have both become important research topics and key techniques in recent adaptive systems. One of the most intriguing problems in the `information age´ is how to filter relevant information from the huge amount of available data. This problem is tackled by using models of the user´s interest in order to increase precision and discriminate interesting information from un-interesting data. However, any user modeling approach suffers from several major drawbacks: User models built by the system need to be inspectable and understandable by the user himself. Secondly, users in general are not willing to give feedback concerning user satisfaction by the delivered results. Without any evidence for the user´s interest, it is hard to induce a hypothetical user model at all. Finally, most current systems do not draw a line of distinction between domain knowledge and user model which makes the adequacy of a user model hard to determine. This thesis presents the novel approach of conceptual user models. Conceptual user models are easy to inspect and understand and allow for the system to explain its actions to the user. It is shown, that ILP can be applied for the task of inducing user models from feedback, and a method for using mutual feedback for sample enlargement is introduced. Results are evaluated independently of domain knowledge within a clear machine learning problem definition. The whole concept presented is realized in a meta web search engine called OySTER.

The main contributions of this thesis revolve around development of an integrated conversational recommendation system, combining data and information models with community network and interactions to leverage multi-modal information access. We have developed a real time conversational information access community agent that leverages community knowledge by pushing relevant recommendations to users of the community. The recommendations are delivered in the form of web resources, past conversation and people to connect to. The information agent (cobot, for community/ collaborative bot) monitors the community conversations, and is 'aware' of users' preferences by implicitly capturing their short term and long term knowledge models from conversations. The agent leverages from health and medical domain knowledge to extract concepts, associations and relationships between concepts; formulates queries for semantic search and provides socio-semantic recommendations in the conversation after applying various relevance filters to the candidate results. The agent also takes into account users' verbal intentions in conversations while making recommendation decision. One of the goals of this thesis is to develop an innovative approach to delivering relevant information using a combination of social networking, information aggregation, semantic search and recommendation techniques. The idea is to facilitate timely and relevant social information access by mixing past community specific conversational knowledge and web information access to recommend and connect users with relevant information. Language and interaction creates usable memories, useful for making decisions about what actions to take and what information to retain. Cobot leverages these interactions to maintain users' episodic and long term semantic models. The agent analyzes these memory structures to match and recommend users in conversations by matching with the contextual information need. The social feedback on the recommendations is registered in the system for the algorithms to promote community preferred, contextually relevant resources. The nodes of the semantic memory are frequent concepts extracted from user's interactions. The concepts are connected with associations that develop when concepts co-occur frequently. Over a period of time when the user participates in more interactions, new concepts are added to the semantic memory. Different conversational facets are matched with episodic memories and a spreading activation search on the semantic net is performed for generating the top candidate user recommendations for the conversation. The tying themes in this thesis revolve around informational and social aspects of a unified information access architecture that integrates semantic extraction and indexing with user modeling and recommendations.