This paper describes the context-aware mobile tourist application COMPASS that adapts its services to the user's needs based on both the user's interests and his current context. In order to provide context-aware recommendations, a recommender system has been integrated with a contextaware application platform. We describe how this integration has been accomplished and how users feel about such an adaptive tourist application.

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In this paper, we report on a study that explores the contribution of social tags, professional metadata and automatically generated metadata to the retrieval process. In this study, 194 participants tagged a total of 115 videos, while another 140 participants searched the video collection for answers to eight questions. The results show that in the current context, social tags yield an effective retrieval process, whereas automatically generated metadata do not. To put this result in perspective, participants' search strategies were primarily guided by the search tasks, instead of metadata elements. We have found some evidence that social tagging is effective, as the same terminology was used in the retrieval process as in the process of assigning metadata.

In this paper we present a web services-based platform that facilitates and speeds up the development and deployment of context-aware, integrated mobile speech and data applications. The platform is capable of handling different types of context and offers sophisticated personalization mechanisms. To illustrate the usefulness of the platform and to validate the claim that cross-platform application development, in particular mobile, context-aware applications, is easier and faster with web services technologies, we present a demonstration application. It serves tourists with interesting information and services in their specific context, and contributes to the achievement of their current goals. Finally, we present a number of problems that we experienced in the implementation process as well as the feedback that we received from real users who tested our application.

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