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The multimedia content delivery chain poses today many challenges. There are increasing terminal diversity, network heterogeneity and the pressure to satisfy the user preferences. The situation encourages the need for the customized contents in order to provide the user in the best possible experience. In this paper, we address the problem of multimedia(More)
Context-aware technologies can make e-learning services smarter and more efficient since context-aware services are based on the user's behavior. To add those technologies into existing e-learning services, a service architecture model is needed to transform the existing e-learning environment, which is situation-aware, into the environment that understands(More)
Mobile and ubiquitous computing devices are transforming the way that learners study. But most of learning contents, designed for desktop, are not suitable for headheld devices. This paper presents ALVC (Adaptation Learning Video Content), an architecture that produces secure, portable and personalization e-learning contents for generic mobile device.
The recommendation system are widely adopted in today’s mainstream online sharing services, providing useful prediction of user’s rating or user’s preferences of sharing items (such as products, movies, books, and news articles). A key challenge of recommendation systems in sharing economy is to employ prediction algorithms to estimate the matching items(More)
Advances in technology for multimedia services have led to a tremendous growth of video contents and accelerated the need to analyze and understand video content. An analysis of sports video, for example, has been a hot research area to identify a number of potential items: player and ball. For the efforts, this paper shows a Cognitive TV framework for the(More)
Personalized video adaptation is expected to satisfy individual users' needs on video content. Multimedia data mining plays a significant role of video annotation to meet users' preference on video content. In this paper, a comprehensive solution for personalized video adaptation is proposed based on video content mining. Video content mining targets both(More)
Despite the increasing importance gained by enterprise standards in the past few years, and the unquestionable goals reached (mainly regarding interoperability among learning enterprise model) current enterprise standards are yet not sufficiently aware of the context of the user. This means that only a limited support for adaptation regarding individual(More)