An information filtering (IF) system monitors an incoming document stream to find the documents that match the information needs specified by the user profiles. To learn to use the user profiles effectively is one of the most challenging tasks when developing an IF system. With the document selection criteria better defined based on the users’ needs, filtering large streams of information can be more efficient and effective. To learn the user profiles, term-based approaches have been widely used in the IF community because of their simplicity and directness. Term-based approaches are relatively well established. However, these approaches have problems when dealing with polysemy and synonymy, which often lead to an information overload problem. Recently, pattern-based approaches (or Pattern Taxonomy Models (PTM) [160]) have been proposed for IF by the data mining community. These approaches are better at capturing sematic information and have shown encouraging results for improving the effectiveness of the IF system. On the other hand, pattern discovery from large data streams is not computationally efficient. Also, these approaches had to deal with low frequency pattern issues. The measures used by the data mining technique (for example, “support” and “confidences”) to learn the profile have turned out to be not suitable for filtering. They can lead to a mismatch problem. This thesis uses the rough set-based reasoning (term-based) and pattern mining approach as a unified framework for information filtering to overcome the aforementioned problems. This system consists of two stages - topic filtering and pattern mining stages. The topic filtering stage is intended to minimize information overloading by filtering out the most likely irrelevant information based on the user profiles. A novel user-profiles learning method and a theoretical model of the threshold setting have been developed by using rough set decision theory. The second stage (pattern mining) aims at solving the problem of the information mismatch. This stage is precision-oriented. A new document-ranking function has been derived by exploiting the patterns in the pattern taxonomy. The most likely relevant documents were assigned higher scores by the ranking function. Because there is a relatively small amount of documents left after the first stage, the computational cost is markedly reduced; at the same time, pattern discoveries yield more accurate results. The overall performance of the system was improved significantly. The new two-stage information filtering model has been evaluated by extensive experiments. Tests were based on the well-known IR bench-marking processes, using the latest version of the Reuters dataset, namely, the Reuters Corpus Volume 1 (RCV1). The performance of the new two-stage model was compared with both the term-based and data mining-based IF models. The results demonstrate that the proposed information filtering system outperforms significantly the other IF systems, such as the traditional Rocchio IF model, the state-of-the-art term-based models, including the BM25, Support Vector Machines (SVM), and Pattern Taxonomy Model (PTM).

[pt] Hoje em dia e-learning está se tornando mais importante por possibilitar a disseminação de conhecimento e informação através da internet de uma forma mais rápida e menos dispendiosa. Consequentemente, de modo a filtrar o que é mais relevante e/ou de interesse do usuário, arquiteturas e técnicas de personalização vêm sendo abordadas. Dentre as muitas possibilidades de personalização existentes, a que lida com acessibilidade está se tornando essencial, pois garante que uma grande variedade de usuários possa ter acesso à informação conforme suas necessidades e características. Acessibilidade não é apenas garantir que pessoas com alguma deficiência, ou dificuldade, possam ter acesso à informação, apesar de ser importante e eventualmente ser uma exigência legal. Acessibilidade é também garantir que uma larga variedade de usuários e interfaces possam obter acesso à informação, maximizando assim a audiência potencial. Esta dissertação apresenta uma extensão do LORIS, um sistema de integração de repositórios de objetos de aprendizagem, descrevendo as alterações na sua arquitetura para ser capaz de lidar com acessibilidade e reconhecer diferentes versões de um mesmo objeto de aprendizagem, permitindo assim que um usuário execute uma consulta considerando seu perfil e preferências. Foi desenvolvido um protótipo dos serviços descritos na arquitetura utilizando serviços Web e navegação facetada, bem como padrões web, de e-learning e de acessibilidade. O uso de serviços Web e de padrões visa promover flexibilidade e interoperabilidade, enquanto a navegação facetada, como implementada, permite que o usuário aplique múltiplos filtros aos resultados da consulta sem a necessidade de re-submetê-la. / [en] Nowadays e-learning is becoming more important as it makes possible the dissemination of knowledge and information through the internet in a faster and costless way. Consequently, in order to filter what is more relevant and/or of users interest, architectures and personalization techniques have been raised. Among the many existing possibilities of personalization, the one that deals with accessibility is becoming essential because it guarantees that a wide variety of users may have access to the information according to their preferences and needs. Accessibility is not just about ensuring that disabled people can access information, although this is important and may be a legal requirement. It is also about ensuring that the wide variety of users and devices can all gain access to information, thereby maximizing the potential audience. This dissertation presents an extension of LORIS, an integration system of learning object repositories, describing the changes on its architecture to make it able to deal with accessibility and to recognize different versions of the same learning object, thus allowing a user to execute a query considering his/her preferences and needs. A prototype of the services that are described in the architecture was developed using web services and faceted navigation, as well as e-learning and accessibility standards. The use of web services and standards aims at providing flexibility and interoperability, while the faceted navigation, as implemented, allows the user to apply multiple filters to the query results without the need to resubmit it.

Les moteurs de recherche, largement utilisés dans différents domaines, sont devenus la principale source d'information pour de nombreux utilisateurs. Cependant, les Systèmes de Recherche d'Information (SRI) font face à de nouveaux défis liés à la croissance et à la diversité des données disponibles. Un SRI analyse la requête soumise par l'utilisateur et explore des collections de données de nature non structurée ou semi-structurée (par exemple : texte, image, vidéo, page Web, etc.) afin de fournir des résultats qui correspondent le mieux à son intention et ses intérêts. Afin d'atteindre cet objectif, au lieu de prendre en considération l'appariement requête-document uniquement, les SRI s'intéressent aussi au contexte de l'utilisateur. En effet, le profil utilisateur a été considéré dans la littérature comme l'élément contextuel le plus important permettant d'améliorer la pertinence de la recherche. Il est intégré dans le processus de recherche d'information afin d'améliorer l'expérience utilisateur en recherchant des informations spécifiques. Comme le facteur temps a gagné beaucoup d'importance ces dernières années, la dynamique temporelle est introduite pour étudier l'évolution du profil utilisateur qui consiste principalement à saisir les changements du comportement, des intérêts et des préférences de l'utilisateur en fonction du temps et à actualiser le profil en conséquence. Les travaux antérieurs ont distingué deux types de profils utilisateurs : les profils à court-terme et ceux à long-terme. Le premier type de profil est limité aux intérêts liés aux activités actuelles de l'utilisateur tandis que le second représente les intérêts persistants de l'utilisateur extraits de ses activités antérieures tout en excluant les intérêts récents. Toutefois, pour les utilisateurs qui ne sont pas très actifs dont les activités sont peu nombreuses et séparées dans le temps, le profil à court-terme peut éliminer des résultats pertinents qui sont davantage liés à leurs intérêts personnels. Pour les utilisateurs qui sont très actifs, l'agrégation des activités récentes sans ignorer les intérêts anciens serait très intéressante parce que ce type de profil est généralement en évolution au fil du temps. Contrairement à ces approches, nous proposons, dans cette thèse, un profil utilisateur générique et sensible au temps qui est implicitement construit comme un vecteur de termes pondérés afin de trouver un compromis en unifiant les intérêts récents et anciens. Les informations du profil utilisateur peuvent être extraites à partir de sources multiples. Parmi les méthodes les plus prometteuses, nous proposons d'utiliser, d'une part, l'historique de recherche, et d'autre part les médias sociaux. / Recently, search engines have become the main source of information for many users and have been widely used in different fields. However, Information Retrieval Systems (IRS) face new challenges due to the growth and diversity of available data. An IRS analyses the query submitted by the user and explores collections of data with unstructured or semi-structured nature (e.g. text, image, video, Web page etc.) in order to deliver items that best match his/her intent and interests. In order to achieve this goal, we have moved from considering the query-document matching to consider the user context. In fact, the user profile has been considered, in the literature, as the most important contextual element which can improve the accuracy of the search. It is integrated in the process of information retrieval in order to improve the user experience while searching for specific information. As time factor has gained increasing importance in recent years, the temporal dynamics are introduced to study the user profile evolution that consists mainly in capturing the changes of the user behavior, interests and preferences, and updating the profile accordingly. Prior work used to discern short-term and long-term profiles. The first profile type is limited to interests related to the user's current activities while the second one represents user's persisting interests extracted from his prior activities excluding the current ones. However, for users who are not very active, the short-term profile can eliminate relevant results which are more related to their personal interests. This is because their activities are few and separated over time. For users who are very active, the aggregation of recent activities without ignoring the old interests would be very interesting because this kind of profile is usually changing over time. Unlike those approaches, we propose, in this thesis, a generic time-sensitive user profile that is implicitly constructed as a vector of weighted terms in order to find a trade-off by unifying both current and recurrent interests. User profile information can be extracted from multiple sources. Among the most promising ones, we propose to use, on the one hand, searching history. Data from searching history can be extracted implicitly without any effort from the user and includes issued queries, their corresponding results, reformulated queries and click-through data that has relevance feedback potential. On the other hand, the popularity of Social Media makes it as an invaluable source of data used by users to express, share and mark as favorite the content that interests them.

När Windows Vista introducerades förändrades mappstrukturen för hur användarprofilen sparas jämfört med tidigare Windowsversioner såsom Windows XP. Denna rapport undersöker kompatibilitetsproblem med Roaming User Profiles mellan äldre och nyare versioner av operativsystemet. Syftet med rapporten var att utreda vilka problem som kan uppstå, vad det gäller Roaming User Profiles, vid en övergång från Windows XP till Windows Vista eller 7. Undersökningen genomfördes med hjälp av laborationer, litteratur och tester för att hitta problemen såväl som lösningar till dem. Resultatet visar att profiler skapade med Windows XP inte följer med till Windows Vista eller 7 utan det skapas sammanlagt två olika profiler, en för det äldre och en för det nyare operativsystemet. Ett skript som kopierar en användares filer från Windows XP till Vista/7 utformades därför. Slutligen presenterades en handlingsplan med olika alternativ vid en övergång från Windows XP till den nyare generationen av operativsystemen i Windowsfamiljen. Folder Redirection är en väl fungerande lösning dock går funktionaliteten som Roaming User Profiles erbjuder förlorad eftersom man endast får en uppmappning av bl.a. ”Mina Dokument” och ”Start Menu”.

Les travaux présentés dans cette thèse rentrent dans le cadre de la Recherche d'Information (RI) et s'intéressent à une des questions de recherche actuellement en vogue dans ce domaine: la prise en compte du contexte de l'utilisateur pendant sa quête de l'information pertinente. Nous proposons une approche originale de reformulation automatique de requêtes basée sur le profil utilisateur et sa tâche actuelle. Plus précisément, notre approche tient compte deux éléments du contexte, les centres d'intérêts de l'utilisateur (son profil) et la tâche qu'il réalise, pour suggérer des requêtes appropriées à son contexte. Nous proposons, en particulier, toute une démarche originale permettant de bien interpréter et réécrire la requête initiale en fonction des activités réalisées dans la tâche courante de l'utilisateur.Nous considérons qu'une tâche est jalonnée par des activités, nous proposons alors d'interpréter le besoin de l'utilisateur, représenté initialement par la requête, selon ses activités actuelles dans la tâche (et son profil) et de suggérer des reformulations de requêtes appropriées à ces activités.Une implémentation de cette approche est faite, et elle est suivie d’une étude expérimentale. Nous proposons également une procédure d'évaluation qui tient compte l'évaluation des termes d'expansion, et l'évaluation des résultats retournés en utilisant les requêtes reformulées, appelés SRQ State Reformulated Query. Donc, trois facteurs d’évaluation sont proposés sur lesquels nous nous appuierons pour l'analyse et l'évaluation des résultats. L’objective est de quantifier l'amélioration apportée par notre système dans certains contextes par rapport aux autres systèmes. Nous prouvons que notre approche qui prend en compte la tâche actuelle de l'utilisateur est effectivement plus performante que les approches basées, soit uniquement sur la requête initiale, ou encore celle basée sur la requête reformulée en considérant uniquement le profil de l'utilisateur. / Access to relevant information adapted to the needs and the context of the user is areal challenge in Web Search, owing to the increases of heterogeneous resources andthe varied data on the web. There are always certain needs behind the user query,these queries are often ambiguous and shortened, and thus we need to handle thesequeries intelligently to satisfy the user’s needs. For improving user query processing,we present a context-based hybrid method for query expansion that automaticallygenerates new reformulated queries in order to guide the information retrieval systemto provide context-based personalized results depending on the user profile andhis/her context. Here, we consider the user context as the actual state of the task thatthe user is undertaking when the information retrieval process takes place. Thus StateReformulated Queries (SRQ) are generated according to the task states and the userprofile which is constructed by considering related concepts from existing concepts ina domain ontology. Using a task model, we will show that it is possible to determinethe user’s current task automatically. We present an experimental study in order toquantify the improvement provided by our system compared to the direct querying ofa search engine without reformulation, or compared to the personalized reformulationbased on a user profile only. The Preliminary results have proved the relevance of ourapproach in certain contexts.

Article publié dans le journal « Journal of Information Security Research ». March 2012. / Chaque année, le nombre d’utilisateurs des réseaux sociaux augmente à une très grande vitesse. Des milliers de comptes usagés incluant des données privées sont créés quotidiennement. Un nombre incalculable de données privées et d'informations sensibles sont ainsi lues et partagées par les différents comptes. Ceci met en péril la vie privée et la sécurité de beaucoup d’utilisateurs de ces réseaux sociaux. Il est donc crucial de sensibiliser ces utilisateurs aux dangers potentiels qui les guettent. Nous présentons Protect_U (Hélou, Gandouz et al. 2012), un système de protection de la vie privée des utilisateurs de Facebook. Protect_U analyse le contenu des profils des utilisateurs et les classes selon quatre niveaux de risque : Low risk, medium risk, risky and critical. Il propose ensuite des recommandations personnalisées pour leur permettre de rendre leurs comptes plus sécuritaires. Pour ce faire, il fait appel à deux modèles de protection : local et communautaire. Le premier utilise les données personnelles de l’utilisateur afin de lui proposer des recommandations et le second recherche ses amis de confiance pour les inciter à participer à l’amélioration de la sécurité de son propre compte. / Social networking sites have experienced a steady and dramatic increase in the number of users over the past several years. Thousands of user accounts, each including a significant amount of private data, are created daily. As such, an almost countless amount of sensitive and private information is read and shared across the various accounts. This jeopardizes the privacy and safety of many social network users and mandates the need to increase the users’ awareness about the potential hazards they are exposed to on these sites. We introduce Protect_U (Hélou, Gandouz et al. 2012), a privacy protection system for Facebook users. Protect_U analyzes the content of user profiles and ranks them according to four risk levels: Low Risk, Medium Risk, Risky and Critical. The system then suggests personalized recommendations designed to allow users to increase the safety of their accounts. In order to achieve this, Protect_U draws upon both the local and community-based protection models. The first model uses a Facebook user’s personal data in order to suggest recommendations, and the second seeks out the user’s most trustworthy friends to encourage them to help improve the safety of his/her account.

Nous présentons dans cette thèse notre travail dans le domaine de la visualisation. Nous nous sommes intéressés au problème de la génération des bulletins météorologiques. Étant donné une masse énorme d’information générée par Environnement Canada et un utilisateur, il faut lui générer une visualisation personnalisée qui répond à ses besoins et à ses préférences. Nous avons développé MeteoVis, un générateur de bulletin météorologique. Comme nous avons peu d’information sur le profil de l’utilisateur, nous nous sommes basés sur les utilisateurs similaires pour lui calculer ses besoins et ses préférences. Nous utilisons l'apprentissage non supervisé pour regrouper les utilisateurs similaires. Nous calculons le taux de similarité des profils utilisateurs dans le même cluster pour pondérer les besoins et les préférences. Nous avons mené, avec l’aide d'utilisateurs n’ayant aucun rapport avec le projet, des expériences d'évaluation et de comparaison de notre outil par rapport à celui utilisé actuellement par Environnement Canada. Les résultats de cette évaluation montrent que les visualisation générées par MeteoVis sont de loin meilleures que les bulletins actuels préparés par EC. / We present our work in this thesis in the field of information visualization. We dealt with the problem of the generation of weather forecasts reports. Given the huge amount of information produced by Environment Canada and a wide variety of users, it must generate a customized visualization that meets their needs and preferences. We developed MeteoVis, a weather report generator. Given that we have little information on the user profile, we relied on the choices made by similar users to calculate the needs and preferences of a user. We use unsupervised machine learning techniques to group similar users . We compute a degree of similarity of user profiles in the same cluster to determine the needs and preferences. We conducted, with the help of external users experiments for evaluating and comparing our tool with the current site of Environment Canada. The evaluation results show that the visualizations generated by MeteoVis are significantly better than the current bulletins prepared by EC.

Chaque année, le nombre d’utilisateurs des réseaux sociaux augmente à une très grande vitesse. Des milliers de comptes usagés incluant des données privées sont créés quotidiennement. Un nombre incalculable de données privées et d'informations sensibles sont ainsi lues et partagées par les différents comptes. Ceci met en péril la vie privée et la sécurité de beaucoup d’utilisateurs de ces réseaux sociaux. Il est donc crucial de sensibiliser ces utilisateurs aux dangers potentiels qui les guettent. Nous présentons Protect_U (Hélou, Gandouz et al. 2012), un système de protection de la vie privée des utilisateurs de Facebook. Protect_U analyse le contenu des profils des utilisateurs et les classes selon quatre niveaux de risque : Low risk, medium risk, risky and critical. Il propose ensuite des recommandations personnalisées pour leur permettre de rendre leurs comptes plus sécuritaires. Pour ce faire, il fait appel à deux modèles de protection : local et communautaire. Le premier utilise les données personnelles de l’utilisateur afin de lui proposer des recommandations et le second recherche ses amis de confiance pour les inciter à participer à l’amélioration de la sécurité de son propre compte. / Social networking sites have experienced a steady and dramatic increase in the number of users over the past several years. Thousands of user accounts, each including a significant amount of private data, are created daily. As such, an almost countless amount of sensitive and private information is read and shared across the various accounts. This jeopardizes the privacy and safety of many social network users and mandates the need to increase the users’ awareness about the potential hazards they are exposed to on these sites. We introduce Protect_U (Hélou, Gandouz et al. 2012), a privacy protection system for Facebook users. Protect_U analyzes the content of user profiles and ranks them according to four risk levels: Low Risk, Medium Risk, Risky and Critical. The system then suggests personalized recommendations designed to allow users to increase the safety of their accounts. In order to achieve this, Protect_U draws upon both the local and community-based protection models. The first model uses a Facebook user’s personal data in order to suggest recommendations, and the second seeks out the user’s most trustworthy friends to encourage them to help improve the safety of his/her account. / Article publié dans le journal « Journal of Information Security Research ». March 2012.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The great advance in the semiconductor industry allowed a increase in the development and marketing of mobile electronic devices. With the expansion of this market, the need for new programming methods and a different view for the development of user interfaces increased. Interfaces that were used before only in desktops and relied on keyboard and mouse interaction are now used in a variety of devices, including cell phones, smartphones and tablets. Often making the use of touch screens as well as by voice commands. Taking into account these aspects of cross-platform and different usability, it becomes apparent the importance of interfaces that adapt "to the environment." With the advent of mobile devices, this particular area became of fundamental importance because this kind of devices has specifics characteristics that are essential to the composition of a satisfactory user interface. So, mobile devices are covering a large variety of features, which makes the interfaces development a very complex task. One way to develop and adapt user interfaces in order to facilitate handling and to reduce stress at the time of use of the device is through the use of user profiles and capabilities of devices. Therefore, that interface is adapted to the user needs and preferences, as well be able to fully adapt to the device features. Considering this assumption, this dissertation aims to present the architecture PIDIM. This architecture goal to assist in the customization and adaptation of user interfaces for mobile devices in pervasive environments. The user interfaces adapted for this process plans to facilitate the use of mobile devices. The proposed approach presents an architecture that uses concepts of Pervasive Computing enabling information access anytime, anyplace, and in any computing device. Besides, it represents data on the user s profile, so that adaptation of the interfaces is entirely focused on the end user. The knowledge representation about the user profile needed for PIDIM architecture modeling is done through ontologies due to the possibility of reuse of stored information. In order to validate and demonstrate the flow of operation of the proposed approach is presented a case study in the literature, which has as scenario the adaptation of user interfaces when it is in motion. / O grande avanço na indústria de semicondutores possibilitou um aumento no desenvolvimento e comercialização de dispositivos eletrônicos móveis. Juntamente com este mercado, cresceu a necessidade de novos métodos de programação e uma visão diferente para criação de interfaces. Interfaces que antes só eram utilizadas em desktops com base de interação teclado e mouse, hoje são utilizadas em diferentes tipos de dispositivos, como celulares, smartphones e tablets, seja utilizadas em telas sensíveis ao toque como também por comando de voz. Levando em conta estes aspectos de multiplataforma e diferentes usabilidades, torna-se visível a importância de interfaces que se adaptem "ao meio". Com o aparecimento dos dispositivos móveis, a área em questão passou a ser de fundamental importância, pois estes dispositivos possuem características particulares fundamentais para a composição de uma interface satisfatória ao usuário. Os dispositivos móveis estão abrangendo uma diversidade grande de características, o que torna o desenvolvimento de uma interface um processo complexo. Uma das formas de desenvolver e adaptar interfaces de usuário de forma a facilitar o manuseio e diminuir o estresse no momento da utilização do dispositivo é através do uso de perfis de usuários e capacidades de dispositivos, fazendo com que a interface se adapte às necessidades e preferências do usuário e consiga se adaptar totalmente às funcionalidades do dispositivo. Considerando isto, este trabalho tem como objetivo apresentar a arquitetura PIDIM, a fim de ajudar na personalização e adaptação de interfaces de usuário para dispositivos móveis em ambientes pervasivos. As interfaces de usuários adaptadas por este processo da arquitetura PIDIM visam facilitar a utilização de dispositivos móveis. A abordagem proposta apresenta uma arquitetura que utiliza conceitos de Computação Pervasiva possibilitando acesso à informação a qualquer hora, lugar, e dispositivo computacional, além de representar dados relativos ao perfil de usuários, para que a adaptação das interfaces seja totalmente focada no usuário final. A representação do conhecimento sobre o perfil do usuário necessário para a modelagem da arquitetura PIDIM é feita através de ontologias devido a possibilidade de reuso das informações armazenadas. A fim de validar e demonstrar o fluxo de funcionamento da abordagem proposta, é apresentado um estudo de caso, encontrado na literatura, o qual possui como cenário a adaptação de interfaces de usuários quando o mesmo se encontra em movimento.

Made available in DSpace on 2016-06-02T19:06:19Z (GMT). No. of bitstreams: 1 6466.pdf: 5791696 bytes, checksum: 534072ee44559aaa0654340ab8533177 (MD5) Previous issue date: 2014-08-14 / One of the core requirements of Ubiquitous Computing is to be user context aware for software solutions developed may be adapted to the different skills and capabilities of users, with regard to physical and cognitive characteristics and interaction preferences. However, the focus of research has been in adapting the systems to different devices. The adaptation to different users profiles still demands further investigation, especially on how to understand and model the physical and cognitive characteristics, and users preferences. It is possible to find several studies that present user profiles models in the literature. Some of these models include a large set of features related to the users. However, only a few works provide an indication of how the information about the user is captured and how the profile already mapped in the model is turned available for applications. Moreover, these models do not take into account the user's interaction needs and preferences, since they only focus on personal information, physiological state, demographics etc. Thus, this work aims to support the flexibility of ubiquitous systems, considering different user profiles, facilitating the collection and delivery of these profiles for ubiquitous computing. To achieve this goal we defined the "Who Am I?" architecture to meet the users diversity by considering their interaction needs and preferences as part of the adopted user profile model; enables the collection of user profiles by means of a collector; and allows communication between the collector and the ubiquitous systems of an interoperable manner. To evaluate the feasibility of this architecture and verify that it meets the diversity of users, a case study was conducted with two scenarios of use. In the first scenario, a bus stop system and the second, a simulation for a smart kitchen was developed. The evaluation of the two software solutions developed was performed with real users and included both technical and emotional aspects. The results indicate that the interaction with both solutions through "Who Am I?" architecture gave satisfaction and motivation in users, and that communication and the adaptation of ubiquitous systems are given appropriately. / Um dos principais requisitos da Computação Ubíqua é ser sensível ao contexto do usuário para que as soluções de software desenvolvidas possam ser capazes de se adaptar às diferentes habilidades e capacidades dos usuários, no que diz respeito às características físicas e cognitivas, e preferências de interação. Todavia, o foco das pesquisas tem sido na adaptação dos sistemas aos diferentes dispositivos. No que se refere à adaptação aos diferentes perfis de usuários ainda é preciso investigar mais, principalmente a forma de conhecer e modelar as características físico-cognitivas e as preferências do usuário. Na literatura, são encontrados vários trabalhos que propõem modelos de perfil de usuário, sendo que alguns destes englobam um conjunto grande de características relacionadas aos usuários. Porém, apenas alguns fornecem uma indicação de como as informações sobre o usuário são capturadas e como o perfil já mapeado é disponibilizado para as aplicações. Além do mais, estes modelos não levam em consideração as necessidades e preferências de interação do usuário, visto que apenas focam em informações pessoais, estado fisiológico, dados demográficos, etc. Desta forma, este trabalho tem como objetivo apoiar a flexibilidade de aplicações ubíquas considerando diferentes perfis de usuários, facilitando a coleta e a oferta desses perfis para a computação ubíqua. Para alcançar esse objetivo definiu-se a arquitetura Who Am I? para atender a diversidade de usuários por considerar suas necessidades e preferências de interação como parte do modelo de perfil de usuário adotado; viabilizar a coleta de perfis de usuários por meio de um coletor; e permitir a comunicação entre o coletor e os sistemas ubíquos de uma forma interoperável. Para avaliar a viabilidade dessa arquitetura e verificar se ela atende à diversidade de usuários, foi realizado um estudo de caso com dois cenários de uso. No primeiro cenário foi desenvolvido um sistema de ponto de ônibus e no segundo, uma simulação para uma cozinha inteligente. A avaliação das duas soluções de software desenvolvidas foi realizada com usuários reais e contemplou tanto aspectos técnicos como emocionais. Os resultados indicam que a interação com ambas por meio da arquitetura Who Am I? proporcionou satisfação e motivação nos usuários e que a comunicação e a adaptação dos sistemas ubíquos se deram de forma adequada.