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NoTube – making TV a medium for personalized interaction
In this paper, we introduce NoTube’s vision on deploying semantics in interactive TV context in order to contextualize distributed applications and lift them to a new level of service that provides context-dependent and personalized selection of TV content. Additionally, lifting content consumption from a single-user activity to a community-based experience in a connected multi-device environment is central to the project. Main research questions relate to (1) data integration and enrichment - how to achieve unified and simple access to dynamic, growing and distributed multimedia content of diverse formats? (2) user and context modeling - what is an appropriate framework for context modeling, incorporating task-, domain and device-specific viewpoints? (3) context-aware discovery of resources - how could rather fuzzy matchmaking between potentially infinite contexts and available media resources be achieved? (4) collaborative architecture for TV content personalization - how can the combined information about data, context and user be put at disposal of both content providers and end-users in the view of creating extremely personalized services under controlled privacy and security policies? Thus, with the grand challenge in mind - to put the TV viewer back in the driver's seat – we focus on TV content as a medium for personalized interaction between people based on a service architecture that caters for a variety of content metadata, delivery channels and rendering devices
Delivery of Personalized and Adaptive Content to Mobile Devices:A Framework and Enabling Technology
Many innovative wireless applications that aim to provide mobile information access are emerging. Since people have different information needs and preferences, one of the challenges for mobile information systems is to take advantage of the convenience of handheld devices and provide personalized information to the right person in a preferred format. However, the unique features of wireless networks and mobile devices pose challenges to personalized mobile content delivery. This paper proposes a generic framework for delivering personalized and adaptive content to mobile users. It introduces a variety of enabling technologies and highlights important issues in this area. The framework can be applied to many applications such as mobile commerce and context-aware mobile services
CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines
Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective.
The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines.
From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research
Personalised trails and learner profiling within e-learning environments
This deliverable focuses on personalisation and personalised trails. We begin by introducing and defining the concepts of personalisation and personalised trails. Personalisation requires that a user profile be stored, and so we assess currently available standard profile schemas and discuss the requirements for a profile to support personalised learning. We then review techniques for providing personalisation and some systems that implement these techniques, and discuss some of the issues around evaluating personalisation systems. We look especially at the use of learning and cognitive styles to support personalised learning, and also consider personalisation in the field of mobile learning, which has a slightly different take on the subject, and in commercially available systems, where personalisation support is found to currently be only at quite a low level. We conclude with a summary of the lessons to be learned from our review of personalisation and personalised trails
Understanding user experience of mobile video: Framework, measurement, and optimization
Since users have become the focus of product/service design in last decade, the term User eXperience (UX) has been frequently used in the field of Human-Computer-Interaction (HCI). Research on UX facilitates a better understanding of the various aspects of the user’s interaction with the product or service. Mobile video, as a new and promising service and research field, has attracted great attention. Due to the significance of UX in the success of mobile video (Jordan, 2002), many researchers have centered on this area, examining users’ expectations, motivations, requirements, and usage context. As a result, many influencing factors have been explored (Buchinger, Kriglstein, Brandt & Hlavacs, 2011; Buchinger, Kriglstein & Hlavacs, 2009). However, a general framework for specific mobile video service is lacking for structuring such a great number of factors. To measure user experience of multimedia services such as mobile video, quality of experience (QoE) has recently become a prominent concept. In contrast to the traditionally used concept quality of service (QoS), QoE not only involves objectively measuring the delivered service but also takes into account user’s needs and desires when using the service, emphasizing the user’s overall acceptability on the service. Many QoE metrics are able to estimate the user perceived quality or acceptability of mobile video, but may be not enough accurate for the overall UX prediction due to the complexity of UX. Only a few frameworks of QoE have addressed more aspects of UX for mobile multimedia applications but need be transformed into practical measures. The challenge of optimizing UX remains adaptations to the resource constrains (e.g., network conditions, mobile device capabilities, and heterogeneous usage contexts) as well as meeting complicated user requirements (e.g., usage purposes and personal preferences). In this chapter, we investigate the existing important UX frameworks, compare their similarities and discuss some important features that fit in the mobile video service. Based on the previous research, we propose a simple UX framework for mobile video application by mapping a variety of influencing factors of UX upon a typical mobile video delivery system. Each component and its factors are explored with comprehensive literature reviews. The proposed framework may benefit in user-centred design of mobile video through taking a complete consideration of UX influences and in improvement of mobile videoservice quality by adjusting the values of certain factors to produce a positive user experience. It may also facilitate relative research in the way of locating important issues to study, clarifying research scopes, and setting up proper study procedures. We then review a great deal of research on UX measurement, including QoE metrics and QoE frameworks of mobile multimedia. Finally, we discuss how to achieve an optimal quality of user experience by focusing on the issues of various aspects of UX of mobile video. In the conclusion, we suggest some open issues for future study
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