Tailoring the Interaction with Users in Web Stores
User Modeling and User-Adapted Interaction
Faceted metadata for image search and browsing
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Personalized Digital Television: Targeting Programs to Individual Viewers (Human-Computer Interaction Series, 6)
An ontology of time for the semantic web
ACM Transactions on Asian Language Information Processing (TALIP) - Special Issue on Temporal Information Processing
Qualitative decision making in adaptive presentation of structured information
ACM Transactions on Information Systems (TOIS)
Context-orientated news riltering for web 2.0 and beyond
Proceedings of the 15th international conference on World Wide Web
Web 2.0: hypertext by any other name?
Proceedings of the seventeenth conference on Hypertext and hypermedia
An adaptive system for the personalized access to news
AI Communications
/facet: a browser for heterogeneous semantic web repositories
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
Convergence of Web and TV Broadcast Data for Adaptive Content Access and Navigation
AH '08 Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems
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To build high-quality personalized Web applications developers have to deal with a number of complex problems. We look at the growing class of personalized Web Applications that share three characteristic challenges. Firstly, the semantic problem of how to enable content reuse and integration. Another problem is how to move away from a sluggish static interface to a responsive dynamic one as seen in regular desktop applications. The third problem is adapting the system into a multi-device environment. For this class of personalized Web applications we look at an example application, a TV recommender called SenSee, in which we solve these problems in a metadata-driven way. We go into depth in the techniques we used to create a solution for these given problems, where we particularly look at utilizing the techniques of Web Services, Web 2.0 and the Semantic Web. Moreover, we show how these techniques can also be used to improve the core personalization functionality of the application. In this paper we present our experience with SenSee to demonstrate general engineering lessons for this type of applications.