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Artificial Intelligence Review
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Mobile service oriented architectures for NN-queries
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The personalized recommendation with bundling strategy based on product consuming period
CIS'09 Proceedings of the international conference on Computational and information science 2009
Ontology-based user preference modeling for enhancing interoperability in personalized services
UAHCI'07 Proceedings of the 4th international conference on Universal access in human-computer interaction: applications and services
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HCI'07 Proceedings of the 12th international conference on Human-computer interaction: applications and services
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W2GIS'04 Proceedings of the 4th international conference on Web and Wireless Geographical Information Systems
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ER'05 Proceedings of the 24th international conference on Perspectives in Conceptual Modeling
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Usage of mobile phones for personalized healthcare solutions
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
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Mobile devices such as personal digital assistants (PDAs) and mobile phones are in widespread use already today and converging to mobile smart phones. They enable the users to access a wide range of services and information without guiding them through their actual demands. Especially during mass events like the Olympic Games 2008 in Beijing - which was initially the context of our work - a large service space is expected to support all mobile visitors, being athletes, journalists, or spectators. Current approaches tackling such problems are location-based (i.e., location-based services), meaning that a user's location is taken into consideration for service provision, and even context-aware, meaning that beyond location other characteristics of a user's environment are taken into account. Such information obviously helps to deliver relevant information at the right time to the mobile users. Going one step further, a situation-aware system abstracts from the context dimensions by translating specific contexts into logical situations (such as being in the car, in a stadium). Even though many context frameworks have been introduced in the past few years, what is usually missing is the notion of characteristic features of contexts which are invariant during certain time intervals. We refer to such features as situations. Knowing the situation end users are in allows the system to better target the information to be delivered to them. This paper presents the main concepts developed for a platform named FLAME2008, which is able to support its mobile users with personalized situation-aware services in push and pull mode.