Algorithms for clustering data
Algorithms for clustering data
ACM Computing Surveys (CSUR)
IEEE Transactions on Knowledge and Data Engineering
Broadcast Television Services Suited for Mobile Handheld Devices
ICDT '06 Proceedings of the international conference on Digital Telecommunications
An Intelligent TV-Shopping Application that Provides Recommendations
ICTAI '07 Proceedings of the 19th IEEE International Conference on Tools with Artificial Intelligence - Volume 01
Personalized Recommendation over a Customer Network for Ubiquitous Shopping
IEEE Transactions on Services Computing
A Novel Framework for Semantic Annotation and Personalized Retrieval of Sports Video
IEEE Transactions on Multimedia
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Proposed architecture and algorithm for personalized advertising on iDTV and mobile devices
IEEE Transactions on Consumer Electronics
What's on TV tonight? An efficient and effective personalized recommender system of TV programs
IEEE Transactions on Consumer Electronics
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Content personalisation is one of the main aims of the mobile media delivery business models, as a new way to improve the user's experience. In broadcasting networks, the content is sent "one to many", so a complete personalisation where the user may select any content is not possible. But using the mobile bidirectional return channel (e.g. UMTS connection) visual targeted advertising can be performed in a simple way: by off-line storing the advertisement for selectively replacing the normal broadcasted advertisement. In fact, these concepts provide powerful methods to increase the value of the service, mainly in mobile environments. In this article we present a novel intelligent content personalisation system for targeted advertising over mobile broadcasting networks and terminals, based on user profiling and clustering, as a new solution where the use of content personalisation represents the competitive advantage over traditional advertising.