Notre travail concerne les systèmes d’aide à la visite de musée et l’accès au patrimoine culturel. L’objectif est de concevoir des systèmes de recommandation, implémentés sur dispositifs mobiles, pour améliorer l’expérience du visiteur, en lui recommandant les items les plus pertinents et en l’aidant à personnaliser son parcours. Nous considérons essentiellement deux terrains d’application : la visite de musées et le tourisme. Nous proposons une approche de recommandation hybride et sensible au contexte qui utilise trois méthodes différentes : démographique, sémantique et collaborative. Chaque méthode est adaptée à une étape spécifique de la visite de musée. L’approche démographique est tout d’abord utilisée afin de résoudre le problème du démarrage à froid. L’approche sémantique est ensuite activée pour recommander à l’utilisateur des œuvres sémantiquement proches de celles qu’il a appréciées. Enfin l’approche collaborative est utilisée pour recommander à l’utilisateur des œuvres que les utilisateurs qui lui sont similaires ont aimées. La prise en compte du contexte de l’utilisateur se fait à l’aide d’un post-filtrage contextuel, qui permet la génération d’un parcours personnalisé dépendant des œuvres qui ont été recommandées et qui prend en compte des informations contextuelles de l’utilisateur à savoir : l’environnement physique, la localisation ainsi que le temps de visite. Dans le domaine du tourisme, les points d’intérêt à recommander peuvent être de différents types (monument, parc, musée, etc.). La nature hétérogène de ces points d’intérêt nous a poussé à proposer un système de recommandation composite. Chaque recommandation est une liste de points d’intérêt, organisés sous forme de packages, pouvant constituer un parcours de l’utilisateur. L’objectif est alors de recommander les Top-k packages parmi ceux qui satisfont les contraintes de l’utilisateur (temps et coût de visite par exemple). Nous définissons une fonction de score qui évalue la qualité d’un package suivant trois critères : l’appréciation estimée de l’utilisateur, la popularité des points d’intérêt ainsi que la diversité du package et nous proposons un algorithme inspiré de la recherche composite pour construire la liste des packages recommandés. L’évaluation expérimentale du système que nous avons proposé, en utilisant un data-set réel extrait de Tripadvisor démontre sa qualité et sa capacité à améliorer à la fois la précision et la diversité des recommandations. / Our work concerns systems that help users during museum visits and access to cultural heritage. Our goal is to design recommender systems, implemented in mobile devices to improve the experience of the visitor, by recommending him the most relevant items and helping him to personalize the tour he makes. We consider two mainly domains of application : museum visits and tourism. We propose a context-aware hybrid recommender system which uses three different methods : demographic, semantic and collaborative. Every method is adapted to a specific step of the museum tour. First, the demographic approach is used to solve the problem of the cold start. The semantic approach is then activated to recommend to the user artworks that are semantically related to those that the user appreciated. Finally, the collaborative approach is used to recommend to the user artworks that users with similar preferences have appreciated. We used a contextual post filtering to generate personalized museum routes depending on artworks which were recommended and contextual information of the user namely : the physical environment, the location as well as the duration of the visit. In the tourism field, the items to be recommended can be of various types (monuments, parks, museums, etc.). Because of the heterogeneous nature of these points of interest, we proposed a composite recommender system. Every recommendation is a list of points of interest that are organized in a package, where each package may constitute a tour for the user. The objective is to recommend the Top-k packages among those who satisfy the constraints of the user (time, cost, etc.). We define a scoring function which estimates the quality of a package according to three criteria : the estimated appreciation of the user, the popularity of points of interest as well as the diversity of packages. We propose an algorithm inspired by composite retrieval to build the list of recommended packages. The experimental evaluation of the system we proposed using a real world data set crawled from Tripadvisor demonstrates its quality and its ability to improve both the relevance and the diversity of recommendations.

Philosophiae Doctor - PhD / This research study investigates optimization of IRS to individual information needs in order of relevance. The research addressed development of algorithms that optimize the ranking of documents retrieved from IRS. In this thesis, we present two aspects of context-awareness in IR. Firstly, the design of context of information. The context of a query determines retrieved information relevance. Thus, executing the same query in diverse contexts often leads to diverse result rankings. Secondly, the relevant context aspects should be incorporated in a way that supports the knowledge domain representing users’ interests. In this thesis, the use of evolutionary algorithms is incorporated to improve the effectiveness of IRS. A context-based information retrieval system is developed whose retrieval effectiveness is evaluated using precision and recall metrics. The results demonstrate how to use attributes from user interaction behaviour to improve the IR effectiveness

Vývoj v informačním systému neustále zvyšuje nároky na účinnou, efektivní a adaptivní spolupráci mezi komponenty systému, aby se vyrovnal se změnami v systému a zaručil tak nejlepší výkon. K dosažení těchto požadavků byly zavedeny dva hlavní přístupy. Přístup k adaptaci umožňuje informačnímu systému přizpůsobit se změnám v kontextu informací systému a jeho okolního prostředí na základě adaptační strategie. Přístup ke zvyšování informovanosti zase napomáhá sledovat informace o kontextu a rozpoznat změny, které mohou proces adaptace vyvolat. V této práci představujeme obecný kontextově orientovaný model vlastní adaptivní architektury pro podporu softwarového systému s adaptačními funkcemi, které zaručují dostupnost systému, provozní podmínky a výkon. Navíc poskytujeme dvě případové studie v reálném životě jako důkaz konceptu použitelnosti našeho navrhovaného adaptačního přístupu.

Thesis (MTech (Business Information Systems))--Cape Peninsula University of Technology, 2020 / A shared common understanding or context awareness (CA) of IT Audit and Governance among all the internal stakeholders of a business remains an important factor. This context awareness is needed between the business itself, the IT department, and the Audit and Risk functions of the business. The research problem states that there is a lack of shared context awareness among all stakeholders when conducting IT audits and implementing IT Governance. To answer the research questions, a case study research strategy was followed using an International Services Group of companies operating from South Africa. The case study offered a diverse group of companies and vast experience in the South African Services, Trading, and Distribution sector. The diversity of this group of companies made it a perfect candidate for understanding context and the value of context in IT when conducting IT audits. The following research questions were asked: i) What are the factors affecting a shared context understanding among the stakeholders when conducting IT audits and implementing IT Governance? ii) How can a shared context understanding among stakeholders be achieved when conducting IT audits and implementing IT Governance? The aim of the study was to explore the value of context awareness within IT Audit and Governance in order to identify the value of shared context understanding. Data collection was done by means of interviews using semi-structured questionnaires and an interview guide. Qualitative data analysis techniques were adopted for this research. The conclusion of the study highlights the importance of a collective understanding of the business’s context in order to obtain alignment in business, IT, and Audit. It refers to the same or a similar understanding of the business processes; this takes time and is unique on all levels.

Context awareness is an important aspect of pervasive and ubiquitous computing. By utilizing contextual information gathered from the environment, applications can adapt to the user’s specific situation. In this thesis, user context is used to automatically discover multimedia devices and services that can be used by a mobile Session Initiation Protocol (SIP) user agent. The location of the user is captured using various sensing technologies to allow users of our SIP user agent to interact with network attached projectors, speakers, and cameras in a home or office environment. In order to determine the location of the user, we have developed and evaluated a context aggregation framework that gathers and analyzes contextual information from various sources such as passive infrared sensors, infrared beacons, light intensity, and temperature sensors. Once the location of the user is determined, the Service Location Protocol (SLP) is used to search for services. For this purpose, we have implemented a mobile SLP user agent and integrated it with an existing SIP user agent. The resulting mobile SIP user agent is able to dynamically utilize multimedia devices around it without requiring the user to do any manual configuration. This thesis also addressed the challenge of building trust relationship between the user agent and the multimedia services. We propose a mechanism which enables the user agent authenticate service advertisements before starting to redirect media streams. The measurements we have performed indicate that the proposed context aggregation framework provides more accurate location determination when additional sensors are incorporated. Furthermore, the performance measurements indicate that the delay incurred by introducing context awareness to the SIP user agent is acceptable for a small deployment such as home and office environment. In order to realize large scale deployments, future investigations are recommended to further improve the performance of the framework. / Att vara medveten om kontexten är en viktig synpunkt av präglande och allestädes närvarande uppskattning av omgivningen. Genom att utnyttja den kontextuella informationen som samlats in från omgivningen, kan applikationen anpassas till användarens specifika situation. I denna avhandling använder man användarens sammanhang för att automatiskt upptäcka multimedia utrustning och tjänster som kan användas av en mobil Session Initiation Protokoll (SIP) användaragent. Placeringen av användaren mäter man med hjälp av olika sensorer för att låta användare av vår SIP användaragent att interagera med nätverk tillkopplat projektorer, högtalare och kameror i hem eller kontorsmiljöer. För att avgöra var användaren befinner har vi utvecklat och utvärderat en sammanhangsstruktur som samlar in och analyserar innehållsbaserad information från olika källor; passiva infraröda sensorer, infraröd beacons, ljusstyrkan och temperaturgivare. Efter bestämmaning användarens placering den så kallade Service Location Protocol (SLP) användas för att söka efter tjänster. För detta ändamål har vi genomfört en mobil SLP användaragent och integrerat denna med ett befintligt SIP användaragent. Den resulterande i mobil SIP användaragent som dynamiskt kan utnyttja multimedia utrustning runt omkring utan att kräva att användaren skall kunna göra någon manuell konfiguration. Avhandlingen tar även upp den utmaningen som krävs för att bygga förtroende mellan användaragenten och multimedia tjänster. Vi föreslår en mekanism som gör det möjligt för användaragenten att verifiera tjänstannonsering innan man börjar dirigera medieströmmar. Dessutom så indikerar mätningarna av prestanda att fördröjningen som man utsätter den för genom att introducera ”medvetenhet om sammanhanget” till SIP användaragenten är acceptabel på hemma eller i en företagsmiljö. För att stora spridningar skall bli verklighet så rekommenderas det att göra mer forskning för att förbättra prestanda.

Recent advances in technology are changing the way how everyday activities are performed. Technologies in the traffic domain provide diverse instruments of gathering and analysing data for more fuel-efficient, safe, and convenient travelling for both drivers and passengers. In this article, we propose a reference architecture for a context-aware driving assistant system. Moreover, we exemplify this architecture with a real prototype of a driving assistance system called Driving coach. This prototype collects, fuses and analyses diverse information, like digital map, weather, traffic situation, as well as vehicle information to provide drivers in-depth information regarding their previous trip along with personalised hints to improve their fuel-efficient driving in the future. The Driving coach system monitors its own performance, as well as driver feedback to correct itself to serve the driver more appropriately.

In this thesis I address the topic of a non-visual approach for interaction on mobile,as an alternative to their existing visual displays in situations where hands free usageof the device is preferred. The current technology will be examined through existingwork with special attention to its limitations, which user groups are currently using anysort of speech recognition or voice command functions and look at in which scenariosare these the most used and most desired. Then I will examine through interviews whypeople trust or distrust voice interactions and how they feel about the possibilities andlimitations of the technology at hand, how individual users use this currently and wheredo they see the technology in the future. After this I will develop an alternative voiceinteraction concept, and validate it through a set of workshops.

Information på webben konsumeras idag via en mängd heterogena enheter. Faktorer som nätverksunderlag och skärmupplösning påverkar vilken bild som är lämplig att leverera till klienten, då en bild i sitt originaltillstånd på en tekniskt begränsad enhet tar lång tid att hämta samt kräver en stor datamängd. Eftersom surfandet på mobila enheter via mobila nätverk förväntas att öka är en lösning för adaptiv bildladdning relevant. Syftet är att undersöka huruvida en webbtjänst, bestående av en klient och en server, kan avgöra bäst lämpad bildkvalitet att leverera till klienten, baserat på dennes aktuella nätverksprestanda och skärmupplösning. En enhet med lägre skärmupplösning och ett långsammare nätverk berättigar en bild i sämre kvalitet och lägre bildupplösning. Därmed förkortas hämtnings- tiden och datamängden reduceras, vilket bidrar till en förbättrad användarupplevelse.Uppsatsen presenterar och utvärderar flera lösningar för adaptiv bildladdning. Lös- ningarna baseras på två parametrar: bredden på klientens webbläsarfönster samt svarstid mellan klient och server, med hjälp av javascript. Dessa parametrar står till grund för den skalning av storlek och kvalitet som sedan appliceras på bilden. Bilden tillhandahålls klien- ten genom någon av de två leveransmetoderna fördefinierade bilder, där flera olika versioner av bilden lagras på servern, och dynamiska bilder, där bilderna i realtid renderas på servern genom gd-biblioteket i php utifrån på originalbilden. Tre typer av adaptiv bildladdning – kvalitetsadaption, storleksadaption och en kombination av de båda, undersöks med av- seende på tidsåtgång och levererad datamängd. Dessa utvärderas sedan i förhållande till basfallet bestående av originalbilderna.Att använda någon typ av adaptionsmetod är i 14 av 15 fall bättre än att enbart leverera originalbilder. Bäst resultat ger kombinerad adaption på enheter med mindre skärmupp- lösning och långsammare nätverk men är även gynnsamt för enheter med medelsnabba nätverk och enheter med stöd för högre skärmupplösning. Både fördefinierad och dyna- misk leveransmetod ger bra resultat men då den dynamiska leveransmetodens skalbarhet med flera parallella anslutningar inte är känd rekommenderas fördefinierade bilder. / Today, information on the web is consumed via a variety of heterogeneous devices. Factors, such as network connection and screen resolution, affects which image that is the most suitable to deliver to the client. An image in its original condition, in a technically limited device, takes a long time to download and requires a large amount of data. Since the number of devices browsing the internet via mobile networks are expected to increase, a solution for adaptive image loading is needed. The aim of this thesis is to explore whether a web service, consisting of a client and a server, can determine the best suited image that should be delivered to the client. This is based on the client’s current network connection and screen resolution. A device with a lower screen resolution and a slower network connection requires an image of lower quality and lower resolution. Thus, the download time can be shortened and the data volume reduced, contributing to improved user experience.Our adaptive solution is based on two measurements – the width of the client’s browser window and the latency between the client and the server – using javascript. These para- meters are the basis for the scaling of the size and quality which applies to the image. The image is provided to the client by one of the two delivery methods: “predefined images”, where several different versions of the image are stored on the server, and “dynamic images”, where the images are rendered on the server by the gd library in php, based on the original image. Three types of adaptive image loading – quality adaptation, size adaptation and a combination of both, are investigated considering delivery time and the amount of data delivered. These are then evaluated in relation to the base case consisting of the original images.Using some type of adaptation method is in 14 out of 15 cases better than simply delivering the original images. The best results are given by the combined adaption method on devices with smaller screen resolutions and slower network connections, but is also beneficial for devices with medium speed connections and devices that support higher screen resolutions. Both predefined and dynamic delivery methods shows good results, but since the dynamic delivery method’s scalability with multiple concurrent clients is not known, it is recommended to use predefined images.

In this thesis, we examine how Emergent Configurations are formed to manageThings and People for the purpose of achieving the user’s goal of repairing a coffeemachine in the dynamic environment of a smart office. We develop an architecturein the form of requirement and design artifacts as well as a realization of the GoalManager component in the Emergent Configuration Manager which is responsiblefor the forming of Emergent Configurations, using the novel Emergent ConfigurationIoT system engineering approach. To demonstrate the capability of the realizationwe developed multiple case scenarios which correspond to the context dynamicity ofa smart office environment. The results of this study introduce an architecture forthe Goal Manager component and demonstrate that the novel engineering approach,Emergent Configuration, is a feasible way of managing IoT systems in the smart officecategory.

<p dir="ltr">Recognition of human behavior and object status plays a significant role in context-aware applications. Although researchers have explored methods to detect users’ activities, there still exists a research gap where end-users are not able to build personalized applications that accurately recognize their activities in the physical environment. Therefore, in this thesis, to fill the gap, we explore different in-situ context-aware Augmented Reality (AR) applications that leverage hand-object recognition and support users to rapidly author context-aware applications by referring to their activities. We first explore the possibility that end-users develop AR applications with customized freehand interactions and introduce GesturAR, an end-to-end authoring tool that supports users to create freehand AR applications through embodied demonstration and visual programming. Next, we explore hand interactions with physical objects and propose ARnnotate, an AR system enabling end-users to create custom data. To further study context-aware applications with haptic feedback, we present Ubi Edge, an AR authoring tool that allows end-users to customize edges on daily objects as tangible user interface (TUI) inputs to control varied digital functions. We develop an integrated AR device and a vision-based detection workflow to track 3D edges and detect the touch interaction between fingers and edges. Finally, to enable end-users to apply AR applications in different physical environments, we propose AdapTUI, a system that can automatically adapt the geometric-based TUIs in various environments. In summary, our contribution lies in the development of several context-aware AR applications that effectively sense users’ activities and facilitate users’ authoring process intuitively and conveniently.</p>