The Internet has made tremendous progress since its inception. The kingpin has been the transmission control protocol (TCP), which supports a large fraction of communication. With the Internet's wide-spread access, users now have increased expectations. The demands have evolved to an extent which TCP was never designed to support. Since network stacks do not provide the necessary functionality for modern applications, developers are forced to implement them over and over again --- as part of the application or supporting libraries. Consequently, application developers not only bear the burden of developing application features but are also responsible for building networking libraries to support sophisticated scenarios. This leads to considerable duplication of effort. The challenge for TCP in supporting modern use cases is mostly due to limiting assumptions, simplistic communication abstractions, and (once expedient) implementation shortcuts. To further add to the complexity, the limited TCP options space is insufficient to support extensibility and thus, contemporary communication patterns. Some argue that radical changes are required to extend the networks functionality; some researchers believe that a clean slate approach is the only path forward. Others suggest that evolution of the network stack is necessary to ensure wider adoption --- by avoiding a flag day. In either case, we see that the proposed solutions have not been adopted by the community at large. This is perhaps because the cost of transition from the incumbent to the new technology outweighs the value offered. In some cases, the limited scope of the proposed solutions limit their value. In other cases, the lack of backward compatibility or significant porting effort precludes incremental adoption altogether. In this dissertation, we focus on the development of a communication model that explicitly acknowledges the context of the conversation and describes (much of) modern communications. We highlight how the communication stack should be able to discover, interact with and use available resources to compose richer communication constructs. The model is able to do so by using session, flow and endpoint abstractions to describe communications between two or more endpoints. These abstractions provide means to the application developers for setting up and manipulating constructs, while the ability to recognize change in the operating context and reconfigure the constructs allows applications to adapt to the changing requirements. The model considers two or more participants to be involved in the conversation and thus enables most modern communication patterns, which is in contrast with the well-established two-participant model. Our contributions also include an implementation of a framework that realizes such communication methods and enables future innovation. We substantiate our claims by demonstrating case studies where we use the proposed abstractions to highlight the gains. We also show how the proposed model may be implemented in a backwards compatible manner, such that it does not break legacy applications, network stacks, or middleboxes in the network infrastructure. We also present use cases to substantiate our claims about backwards compatibility. This establishes that incremental evolution is possible. We highlight the benefits of context awareness in setting up complex communication constructs by presenting use cases and their evaluation. Finally, we show how the communication model may open the door for new and richer communication patterns. / PHD

User interface design and development for ubiquitous software applications is challenged by the presence of varying contexts. Context comprises of user'­s computing platform, the environment in which the user is interacting with the application and user characteristics which comprise of user's behavior during interaction and user preferences for interface display and interaction. We present a framework for adaptive user interface generation where adaptation occurs when context changes. This framework introduces three new concepts. First, formalization for representing context is introduced. Our design of context specification is unique since it reflects the association of context with level and nature of user interface adaptation. Secondly, user interface generation life cycle is studied and we define a context model on top of task model to introduce the contextual conditions into user interface generation process. Using the context model, user interface designer can specify contextual requirements and its effect on the user interface. Third, context aware adaptation of user interfaces is achieved by mapping context specifications to various levels of user interface generation life cycle. We designed a specification language called rule specification using which the user interface designer can specify the mapping. With the new design of context representation, context model, and rule specification, we demonstrate how changes in contexts adapts task model which in turn adapts the user interface. / Master of Science

This work has two objectives: a) to predict people's future locations, and b) to predict when they will be at given locations. Current location-based applications react to the user's current location. The progression from location-awareness to location-prediction can enable the next generation of proactive, context-predicting applications. Existing location-prediction algorithms predict someone's next location. In contrast, this dissertation predicts someone's future locations. Existing algorithms use a sequence of locations and predict the next location in the sequence. This dissertation incorporates temporal information as timestamps in order to predict someone's location at any time in the future. Sequence predictors based on Markov models have been shown to be effective predictors of someone's next location. This dissertation applies a Markov model to two-dimensional, timestamped location information to predict future locations. This dissertation also predicts when someone will be at a given location. These predictions can support presence or understanding co-workers’ routines. Predicting the times that someone is going to be at a given location is a very different and more difficult problem than predicting where someone will be at a given time. A location-prediction application may predict one or two key locations for a given time, while there could be hundreds of correct predictions for times of the day that someone will be in a given location. The approach used in this dissertation, a heuristic model loosely based on Market Basket Analysis, is the first to predict when someone will arrive at any given location. The models are applied to sparse, WiFi mobility data collected on PDAs given to 275 college freshmen. The location-prediction model predicts future locations with 78-91% accuracy. The temporal-prediction model achieves 33-39% accuracy. If a tolerance of plus/minus twenty minutes is allowed, the prediction rates rise to 77%-91%. This dissertation shows the characteristics of the timestamped, location data which lead to the highest number of correct predictions. The best data cover large portions of the day, with less than three locations for any given timestamp. / Ph. D.

選擇到哪家餐廳用餐的問題，不論旅遊或家居都經常會遇到。大多數的人會先上網，尋找符合自己喜好且評價好的美食。然而網際網路發達，在人人都可上網分享的情況下，造成資訊氾濫超載。使得使用者上網瀏覽資料時，很容易找到不切合需求的資訊。解決此資訊超載的方法之一是餐廳推薦系統。儘管目前有很多的推薦應用程式或是分享平台，諸如TripAdvisor、iPeen愛評網、foursquare…等等，資料豐富但卻沒有針對個人偏好做推薦。 　　本研究有鑒於許多人在品嘗美食之前，會先拍照並在Facebook或Instagram打卡做紀錄、分享給朋友，打卡的次數可能意味著此餐廳的熱門度。且使用者選擇的美食類型偏好也可能受到聚餐目的的影響。因此開發出一款結合社群互動圈以及考量用餐情境的餐廳推薦系統。此系統先利用使用者所選擇的聚餐場合、價位、餐廳類型、熱門商圈等元素篩選出合適的餐廳，再利用Facebook打卡資料取得與使用者偏好相似的好友，依據好友的相似度推算出使用者對餐廳的喜好程度，推薦符合使用者興趣及需求的餐廳，協助使用者能夠更容易地找到自己所喜好的店家。 　　本研究的實作系統，經過評估測試，結果發現結合社群互動圈及考量用餐情境的個人化推薦能讓使用者更容易找到自己所喜好的餐廳，而在推薦內容中顯示好友對餐廳的評論，更有效的幫助使用者作決策。未來本推薦系統所使用之結合情境元素所設計的模式亦可應用至其他領域的推薦平台，如旅遊景點推薦或旅遊住宿推薦。 / Most people face the issue of deciding which restaurant to eat. Searching through the Internet is the first step that people usually do. However the rapid growth of information has overloaded the Internet users, it makes difficult to find the most appropriate information for decision-making. Certainly there are several restaurant recommender systems have been developed to solve the problem, such as TripAdvisor, iPeen, foursquare, etc; but few systems provide personalized and context-based recommendations. 　　The research intends to develop a restaurant recommender system that considers the factors of social network and context. Nowadays, when people eat, they like to take a picture and check in on Facebook or Instagram to share with friends, the numbers of check-in for a restaurant may mean the restaurant’s popularity. In addition, the gathering purpose and personal preferences may also affect the users’ decisions. Therefore the recommender system first used the variables of eating criteria such as place, price, types of food, eating environments to filter restaurants. The system then got the user’s similar friends from check-in data of Facebook. Through calculating friends’ similarity and their preference of restaurants, the recommender system finds the most fitted ones for the user to choose from. 　　The afterward system’s users testing data prove that this personalized and context-based recommendation system provides better information to help the user make their decisions. The same model can be replicated to other domain of recommender platforms.

Submitted by Aline Batista (alinehb.ufpel@gmail.com) on 2018-04-19T12:36:54Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) dissertacao_eduardo_soares_de_abreu.pdf: 4224104 bytes, checksum: fc46a837bb512d7f07fb7941f7cd362d (MD5) / Approved for entry into archive by Aline Batista (alinehb.ufpel@gmail.com) on 2018-04-19T14:43:52Z (GMT) No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) dissertacao_eduardo_soares_de_abreu.pdf: 4224104 bytes, checksum: fc46a837bb512d7f07fb7941f7cd362d (MD5) / Made available in DSpace on 2018-04-19T14:44:01Z (GMT). No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) dissertacao_eduardo_soares_de_abreu.pdf: 4224104 bytes, checksum: fc46a837bb512d7f07fb7941f7cd362d (MD5) Previous issue date: 2017-05-29 / Conselho Nacional de Pesquisa e Desenvolvimento Científico e Tecnológico - CNPq / Nos últimos anos, as técnicas de Reconhecimento de Atividades têm atraído atenção crescente. Entre as muitas aplicações, um interesse especial está no domínio ubíquo da e-Health, onde o reconhecimento automático de atividades é usado em sistemas de reabilitação, gerenciamento de doenças crônicas, monitoramento de idosos, bem como em aplicações de bem-estar pessoal. Esse interesse tem tido como motivação o envelhecimento da população. Este envelhecimento resulta em significativos desafios socioeconômicos no setor da saúde pública, bem como na incidência de doenças crônico-degenerativas, sendo a demência uma das mais preocupantes. Uma alternativa que vem sendo amplamente proposta é a utilização de casas inteligentes (ambiente assistido de vivência), nos quais as residências das pessoas sob tratamento deverão contemplar serviços computacionais que possam auxiliá-las nas suas práticas diárias, de forma o mais transparente possível. Este trabalho tem como acrônimo EXEHDA-AR (EXEHDA-Activity Recognition), e seu objetivo principal é contribuir com o Subsistema de Reconhecimento de Contexto e Adaptação do middleware EXEHDA (Execution Environment for Highly Distributed Applications) capacitando-o para o atendimento das demandas do Reconhecimento de Atividades, explorando para isto uma abordagem baseada em Ciência de Contexto. O EXEHDA-AR explora processamento semântico para prover Reconhecimento de Atividades em Casas Inteligentes, para tanto foram propostos componentes a serem integrados ao middleware EXEHDA, bem como um modelo ontológico. Os dados de contexto coletados são agrupados segundo o conceito de janela de tempo deslizante. Quando avaliado o EXEHDA-AR obteve uma acurácia média de 94,36% no Reconhecimento de Atividades. Estes resultados apontam que métodos baseados em processamento semântico constituem uma alternativa viável para o reconhecimento de Atividades com baixo nível de intrusão, indicando a continuidade dos esforços de pesquisa. / In recent years, the techniques of Activity Recognition have attracted increasing attention. Among the many applications, special interest lies in the ubiquitous domain of e-Health, where automatic activity recognition is used in rehabilitation systems, chronic disease management, elderly monitoring, as well as in personal wellness applications. This interest has been motivated by the aging of the population. This aging results in significant socioeconomic challenges in the public health sector, as well as in the incidence of chronic-degenerative diseases, with dementia being one of the most worrying. An alternative that has been widely proposed is the use of intelligent houses (ambient assisted living), in which the residences of people under treatment should contemplate computational services that can assist them in their daily practices, in the most transparent way possible. This work has the acronym EXEHDA-AR (EXEHDA-Activity Recognition), and its main objective is to contribute with the Context Recognition and Adaptation Subsystem of the EXEHDA (Execution Environment for Highly Distributed Applications) middleware, enabling it to meet the demands Of Activity Recognition, using a Context Awareness approach. The EXEHDA-AR explores semantic processing to provide Activity Recognition in smart home, for which we have proposed components to be integrated with the EXEHDA middleware as well as an ontological model. The collected context data are grouped according to the concept of time-sliding window. When evaluated the EXEHDA-AR obtained an average accuracy of 94.36% in the Recognition of Activities. These results indicate that methods based on semantic processing constitute a viable alternative for the Recognition of Activities with low level of intrusion, indicating the continuity of research efforts.

Les technologies et services mobiles font aujourd'hui partie de notre vie quotidienne grâce notamment aux ordiphones et ardoises numériques. Nous vivons actuellement la réalisation de la vision de Marc Weiser. Les fonctionnalités et les services rendus prennent le dessus sur les objets techniques. Dans cette thèse, nous nous intéressons à un type particulier d'applications informatiques: les jeux vidéo. Comme d'autres secteurs, les jeux vidéo doivent prendre en compte la révolution mobile, pour se réinventer et intéresser des joueurs. Cependant, les jeux sur support mobiles doivent faire face au problème du changement des conditions de jeu du joueur. Nous pouvons parler de contexte du joueur.L'objectif de cette thèse est de proposer un modèle pour la conception de jeu auto-adaptatif au contexte du joueur. Ce modèle doit être générique et permettre la création de jeux vidéo qui sont capables de modifier les activités et objectifs qu'ils proposent en fonction du contexte courant du joueur. Notre proposition se constitue de deux éléments clefs. Le premier consiste en un modèle générique des activités et des objectifs d'un jeu vidéo que nous avons appelé «composant de gameplay». Ce modèle est une formalisation du concept de boucle de jeu objectif, challenge, récompense. Ce modèle nous permet de représenter les objectifs et activités du jeu sous la forme d'un arbre. Le deuxième élément est un modèle de détection des arbres compatibles avec un contexte courant. Ce modèle se base sur des règles de contexte qui sont associées aux nœuds de l'arbre. Notre démarche consiste ensuite à vérifier que l'objectif représenté par la racine de l'arbre peut être atteint dans le contexte courant. Pour valider notre approche, nous avons réalisé une expérimentation en laboratoire. Nous avons également utilisé notre expérience sur l'utilisation des composants de gameplay dans un contexte industriel. / Nowadays, the technologies and mobiles services are a part of our daily life thanks to smartphones and tablet computers. Currently, we live the realisation of Weiser's vision. The features and services provided are more important than technical objects.In this thesis, we are interested in a kind of computer applications: video games. Like other sectors, video games have to deal with mobile revolution in order to reinvent themselves and to interest players. However, video games on mobiles devices have to deal with the variation of playing conditions. We can call these conditions the player's context.The main objective of this thesis is to propose a model for the design of games that are able to adapt to the player's context. This model has to be generic and allow the game to adapt the proposed activities and objectives to the current context.Our proposition has two main elements. The first one is a generic model of the activities and the objectives which are proposed by the game. We have called this model "gameplay component". It is a formalization of the objectif, challenge, reward game loop concept. It allows us to represent a game as a tree.The second element is a model for detecting game tree which are compatible with a defined context. This model is based on rules which are linked with the nodes of the game tree. Our approach consist of checking that the objective which is given by the root of the game tree can be reached in the current context.In order to valid our approach, we have conducted a laboratory experimentation. We have also used our experience about using of gameplay component in a industrial context in order to do a case study.

The great amount of generated data from IoT infrastructures in Smart Cities, if properly leveraged, presents the opportunity to shift towards more sustainable practices in rapidly increasing urban areas. Reasoning upon this data in a proactive way, by avoiding unwanted future events before they occur, leads to more efficient services. For a system to do so, a robust reasoning model, able to anticipate upcoming events and pick the most suitable adaptation option is needed. Recently deployed smart waste management systems for monitoring and planning purposes report substantial cost-savings and carbon footprint reductions, however, such systems can be further enhanced by integrating proactive capabilities. This work proposes a novel reasoning model and system architecture called ProAdaWM for more effective and efficient waste operations when faced with severe weather events. A Bayesian Network and Utility Theory, as the basis of Decision Theory, are utilized to model the uncertainties and handle how the system adapts; the proposed model utilizes weather information and data from bin level sensor for reasoning. The approach is validated through the implementation of a prototype and the conduction of a case study; the results demonstrate the expected behavior.

Master of Philosophy (Architecture) / Context-aware computing is a mobile computing paradigm in which applications can discover, use, and take advantage of contextual information, such as the location, tasks and preferences of the user, in order to adapt their behaviour in response to changing operating environments and user requirements. A problem that arises is the inability to respond to contextual information that cannot be classified into any known context. Many context-aware applications require all discovered contextual information to exactly match a type of context, otherwise the application will not react responsively. The ability to learn and recall contexts based on the contextual information discovered has not been very well addressed by previous context-aware applications and research. The aim of this thesis is to develop a component middleware technology for mobile computing devices for the discovery and capture of contextual information, using the situated reasoning concept of constructive memory. The research contribution of this thesis lies in developing a modified architecture for context-aware systems, using a constructive memory model as a way to learn and recall contexts from previous experiences and application interactions. Using a constructive memory model, previous experiences can be induced to construct potential contexts, given a small amount of learning and interaction. The learning process is able to map the many variations of contextual information currently discovered by the user with a predicted type of context based on what the application has stored and seen previously. It only requires a small amount of contextual information to predict a context, something common context-aware systems lack, as they require all information before a type of context is assigned. Additionally, some mechanism to reason about the contextual information being discovered from past application interactions will be beneficial to induce contexts for future experiences.

Οι τεχνολογικές εξελίξεις των τελευταίων ετών, έχουν αναβαθμίσει τις κινητές συσκευές, από απλά κινητά τηλέφωνα σε συσκευές κινητού υπολογισμού. Οι σύγχρονες κινητές συσκευές είναι πλέον εξοπλισμένες με φωτογραφικούς φακούς υψηλής ανάλυσης, δέκτη GPS, δέκτη WiFi (802.11 b/g/n), κυκλώματα NFC, δυνατότητες σύνδεσης στο διαδίκτυο μέσω δικτύων κινητής τηλεφωνίας (3G/4G), επιταχυνσιόμετρα, αισθητήρες καταγραφής καρδιακών παλμών κ.α. Οι αισθητήρες αυτοί, είναι σε θέση να συλλέγουν πληροφορίες για το πλαίσιο του χρήστη (user’s context), το οποίο συμπεριλαμβάνει πληροφορίες όπως η τοποθεσία του, η τρέχουσα μέρα και ώρα, ο προσανατολισμός της συσκευής, το αν ο χρήστης κινείται και με πόση ταχύτητα, την τρέχουσα δραστηριότητα του χρήστη (π.χ. ομιλία, πληκτρολόγηση κειμένου) κ.α. Επίσης, οι ίδιοι οι χρήστες αποθηκεύουν στις συσκευές όλο και περισσότερες προσωπικές πληροφορίες, όπως το ιστορικό της επικοινωνίας τους, σύντομα μηνύματα, φωτογραφίες, emails, μουσική και βίντεο, υπενθυμίσεις και γεγονότα στο ημερολόγιο κ.α. Ο συνδυασμός του πλαισίου του χρήστη με την κοινωνική πληροφορία του χρήστη, δημιουργούν ένα δυναμικά οριζόμενο πλαίσιο, το κοινωνικό κινητό πλαίσιο του χρήστη (user’s mobile social context). Σκοπός της διδακτορικής διατριβής, είναι η υποστήριξη του χρήστη για την ανάκτηση προσωπικών πληροφοριών από συσκευές κινητού υπολογισμού, με αξιοποίηση του κινητού κοινωνικού πλαισίου. Στα πλαίσια της διδακτορικής διατριβής, ως περίπτωση χρήσης, μελετήθηκε η ανάκτηση επαφών από το χρήστη με σκοπό την επικοινωνία (κλήση, μήνυμα κ.λπ.). Παρόλα αυτά, η μεθοδολογία που ακολουθήθηκε μπορεί να εφαρμοστεί για την ανάκτηση οποιουδήποτε είδους προσωπικής πληροφορίας, όπως φωτογραφίες, βίντεο, μουσική κ.α. Συγκεκριμένα, αφού μελετήθηκαν πραγματικά δεδομένα χρήσης από δύο σύνολα δεδομένων, σχεδιάστηκε και υλοποιήθηκε ένας νέος αλγόριθμος για την πρόβλεψη της μελλοντικής επικοινωνίας του χρήστη συσκευών κινητού υπολογισμού. Στη συνέχεια, έγινε σύγκριση του συγκεκριμένου αλγορίθμου με υπάρχουσες προσεγγίσεις, οι οποίες αναφέρονται στη βιβλιογραφία. Κατόπιν, σχεδιάστηκε και υλοποιήθηκε σύστημα για συσκευές κινητού υπολογισμού το οποίο ενσωματώνει τον προτεινόμενο αλγόριθμο. Παράλληλα, σχεδιάστηκαν, υλοποιήθηκαν και αξιολογήθηκαν, τόσο στο εργαστήριο όσο και με πειράματα πεδίου, υβριδικές προσαρμοστικές διεπαφές για την παρουσίαση των προτάσεων του αλγορίθμου και, γενικότερα, την υποστήριξη ανάκτησης προσωπικής πληροφορίας, όπως οι επαφές, σε συσκευές κινητού υπολογισμού. Αναλυτικότερα, στο πρώτο κεφάλαιο, παρουσιάζεται η τρέχουσα κατάσταση στο πεδίο των συσκευών κινητού υπολογισμού, σε επίπεδο υλικού, σε επίπεδο δικτύων και σε επίπεδο λειτουργικών συστημάτων των συσκευών κινητού υπολογισμού. Επίσης, παρουσιάζεται συνοπτικά η έννοια του context και των context aware συστημάτων. Τέλος, γίνεται μια πρώτη καταγραφή των ερευνητικών θεμάτων της διδακτορικής διατριβής και παρουσιάζεται συνοπτικά η συνεισφορά της. Στο δεύτερο κεφάλαιο, γίνεται μια εκτενής παρουσίαση της τρέχουσας ερευνητικής δραστηριότητας στον τομέα της διδακτορικής διατριβής. Συγκεκριμένα, αναπτύσσονται οι έννοιες του context και των context-aware συστημάτων και στη συνέχεια γίνεται αναφορά στις έννοιες του mobile και social context. Κατόπιν, παρουσιάζονται μεθοδολογίες ανάκτησης και μοντελοποίησης του context, με έμφαση στο context των συσκευών κινητού και διάχυτου υπολογισμού. Στη συνέχεια, παρουσιάζονται χαρακτηριστικά παραδείγματα κινητών context aware συστημάτων, με έμφαση στα context aware συστήματα για τη διαχείριση προσωπικής πληροφορίας σε συσκευές κινητού υπολογισμού και ειδικότερα στη διαχείριση των επαφών και της επικοινωνίας του χρήστη. Τέλος, παρουσιάζονται νέα είδη διεπαφών (adaptive interfaces), οι οποίες προσαρμόζονται στο τρέχον context της συσκευής κινητού υπολογισμού. Στο τρίτο κεφάλαιο, παρουσιάζεται το πρώτο μέρος του ερευνητικού έργου της παρούσας διδακτορική διατριβής. Συγκεκριμένα, παρουσιάζεται η μελέτη και υλοποίηση ενός αλγορίθμου για την ανάκτηση προσωπικής πληροφορίας από συσκευές κινητού υπολογισμού. Ως περίπτωση χρήσης, εστιάσαμε στην ανάκτηση των επαφών. Αρχικά, παρουσιάστηκε ο τρόπος με τον οποίο επιλέξαμε να αναπαραστήσουμε το context του χρήστη. Στη συνέχεια, για να ερευνηθεί ποιες διαστάσεις του context είναι οι σημαντικότερες για την ανάκτηση επαφών, πραγματοποιήθηκε η ανάλυση δύο συνόλων δεδομένων, ενός που συλλέχθηκε στα πλαίσια της διδακτορικής διατριβής και ενός που παραχωρήθηκε από την εταιρία ΝΟΚΙΑ. Κατόπιν, παρουσιάζεται ο σχεδιασμός και η πειραματική αξιολόγηση του αλγορίθμου. Τέλος, παρουσιάζεται η σύγκριση του προτεινόμενου αλγορίθμου με αντίστοιχους αλγορίθμους και προσεγγίσεις της βιβλιογραφίας. Στο τέταρτο κεφάλαιο, παρουσιάζεται η υλοποίηση ενός συστήματος ανάκτησης επαφών σε συσκευές κινητού υπολογισμού. Συγκεκριμένα, υλοποιήθηκε ο αλγόριθμος που παρουσιάστηκε στο προηγούμενο κεφάλαιο και στη συνέχεια σχεδιάστηκαν και υλοποιήθηκαν context aware προσαρμοστικές διεπαφές, για την ανάκτηση επαφών σε συσκευές κινητού υπολογισμού. Στη συνέχεια, παρουσιάζεται η αξιολόγηση του συστήματος που υλοποιήθηκε, με την πραγματοποίηση πειράματος πεδίου, διάρκειας ενός μήνα. Κατά τη διάρκεια του πειράματος, συλλέγονταν ανώνυμα στατιστικά χρήσης του συστήματος, ενώ, στο τέλος του πειράματος, έγινε και συλλογή ποιοτικών δεδομένων, με χρήση ερωτηματολογίων. Στο τελευταίο, πέμπτο, κεφάλαιο, παρουσιάζεται μία σύνοψη της διδακτορικής διατριβής, καταγράφονται τα συμπεράσματα της και γίνεται αναφορά στις μελλοντικές επεκτάσεις του ερευνητικού έργου. / Recent technological advances have transformed the mobile phones from simple communication devices to pervasive computing devices. Today’s mobiles are equipped with a great variety of hardware, such as high definition cameras, GPS receivers, WiFi capabilities, NFC chips, 3G/4G mobile network connections, compass, accelerometers etc. Those sensors collect a huge amount of information about mobile device’s user and her environment (user’s context), for example, the location, current day and time, device’s orientation, if she is on the move and how fast, the current task (e.g. talking, typing text) etc. Besides the automatically generated information, users keep a lot of personal information on their mobile devices like communication history, short messages, photos, emails, music and videos, reminder and calendar events etc. If we combine the user’s context with the stored social information, a dynamic context is created, which can be termed the user’s mobile social context. The aim of this PhD thesis is the exploitation of user’s mobile social context in order to support the extraction of personal information from mobile computing devices. As an example of personal information, this thesis studies the support of user’s communication by extracting the desired contacts. However, the same methodology applies to all kinds of personal information like photos, videos, music etc. First of all, real mobile usage statistics from two different datasets were analyzed in order to design and implement a new prediction algorithm of the future user’s communication on mobile devices. Secondly, a comparison between the proposed algorithm and relative algorithms was conducted. Then, a system for mobile devices that embeds the proposed algorithm was developed. At the same time, adaptive interfaces for the presentation of the proposals of the algorithm were designed and evaluated, conducting both lab and field experiments. Chapter 1 presents the current status in the field of mobile computing devices, in terms of hardware, mobile networks and mobile operating systems. The terms “context” and “context aware” systems are also briefly presented. Finally, Chapter 1 presents the research question of this thesis and its research contribution. Chapter 2 presents the related work in the field. First, the terms “context” and “context aware” are discussed in detail and then the terms of “mobile” and “social context” are introduced. The chapter discusses proposals for retrieving and modeling the user’s context, giving detailed information about the mobile user’s context. Also, in the same chapter, examples of context aware systems are presented, focusing mainly to context aware systems for communication management and contacts retrieval. Finally, novel, adaptive, context aware interfaces are also presented. Chapter 3 presents the first part of the thesis’ research. A new algorithm for the task of contacts retrieval is proposed. In order to choose the proper dimensions of the user’s context for the specific task, an analysis and examination of two different dataset is perfomed. The first dataset is preliminary and it is collected in the context of this thesis. The second one is provided by NOKIA and is the outcome of a large scale initiative that took place in Geneva area of Switzerland, the NOKIA Lausanne Data Collection Campaign. A comparative evaluation of the proposed algorithm against the two mentioned datasets is finally performed. Finally, a comparison of the proposed algorithm with similar approaches and algorithms is presented. In Chapter 4, the design and implementation of a Google Android system for contacts retrieval from mobile computing devices is presented. A set of context aware adaptive interfaces for contacts retrieval was designed and developed, to make use of the algorithm discussed in Chapter 3. These interfaces were tested using a large scale field experiment (1 month duration) in order to evaluate the system in real conditions and with real users. During the experiment, anonymous usage statistics from users were collected and a questionnaire for the qualitative evaluation of our system was also distributed. In the final chapter (chapter 5), the conclusions of the thesis and future work suggestions are presented.

Internet Protocol TV (IPTV) delivers television content to users over IP-based network. Different from the traditional TV services, IPTV platforms provide users with large amount of multimedia contents with interactive and personalized services, including the targeted advertisement, on-demand content, personal video recorder, and so on. IPTV is promising since it allows to satisfy users experience and presents advanced entertainment services. On the other hand, the Next Generation Network (NGN) approach in allowing services convergence (through for instance coupling IPTV with the IP Multimedia Subsystem (IMS) architecture or NGN Non-IMS architecture) enhances users' experience and allows for more services personalization. Although the rapid advancement in interactive TV technology (including IPTV and NGN technologies), services personalization is still in its infancy, lacking the real distinguish of each user in a unique manner, the consideration of the context of the user (who is this user, what is his preferences, his regional area, location, ..) and his environment (characteristics of the users' devices 'screen types, size, supported resolution, '' and networks available network types to be used by the user, available bandwidth, ..') as well as the context of the service itself (content type and description, available format 'HD/SD', available language, ..) in order to provide the adequate personalized content for each user. This advanced IPTV services allows services providers to promote new services and open new business opportunities and allows network operators to make better utilization of network resources through adapting the delivered content according to the available bandwidth and to better meet the QoE (Quality of Experience) of clients. This thesis focuses on enhanced personalization for IPTV services following a user-centric context-aware approach through providing solutions for: i) Users' identification during IPTV service access through a unique and fine-grained manner (different from the identification of the subscription which is the usual current case) based on employing a personal identifier for each user which is a part of the user context information. ii) Context-Aware IPTV service through proposing a context-aware system on top of the IPTV architecture for gathering in a dynamic and real-time manner the different context information related to the user, devices, network and service. The context information is gathered throughout the whole IPTV delivery chain considering the user domain, network provider domain, and service/content provider domain. The proposed context-aware system allows monitoring user's environment (devices and networks status), interpreting user's requirements and making the user's interaction with the TV system dynamic and transparent. iii) Personalized recommendation and selection of IPTV content based on the different context information gathered and the personalization decision taken by the context-aware system (different from the current recommendation approach mainly based on matching content to users' preferences) which in turn highly improves the users' Quality of Experience (QoE) and enriching the offers of IPTV services