PLIS+: A Rule-Based Personalized Location Information System

I. Viktoratos, A. Tsadiras, N. Bassiliades, “PLIS+: A Rule-Based Personalized Location Information System”, Proc. of the RuleML2012@ECAI Challenge, at the 6th International Symposium on Rules, Hassan Ait-Kaci, Yuh-Jong Hu, Grzegorz J. Nalepa, Monica Palmirani, Dumitru Roman (Ed.), CEUR Workshop Proceedings, Vol-874, Montpellier, France, August 2012

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Author(s): I. Viktoratos, A. Tsadiras, Nick Bassiliades

Appeared In: Proc. of the RuleML2012@ECAI Challenge, at the 6th International Symposium on Rules, Hassan Ait-Kaci, Yuh-Jong Hu, Grzegorz J. Nalepa, Monica Palmirani, Dumitru Roman (Ed.), CEUR Workshop Proceedings, Vol-874, Montpellier, France, August 27-31, 2012, 2012.

Keywords: RuleML, Rules, Location Based Services, Context, Points of Interest, Jess.

Tags:

2012, Bassiliades, Tsadiras, Viktoratos

Abstract: In this paper, the idea of providing personalized, location-based information services via rule-based policies is demonstrated. After a short introduction, an innovative Personalized Location Information System (PLIS+) is designed and implemented. PLIS+ delivers personalized and contextualized information to users according to rule-based policies. More specifically, many categories of points of interest (for example shops, restaurants) have rule-based policies to expose and deploy their marketing strategy on special offers, discounts, etc. PLIS+ evaluates these rules on-the-fly and delivers personalized information according to the user’s context and the corresponding rules fired within this context. After discussing the design and the implementation of PLIS+, illustrative examples of PLIS+ functionality are presented. As a result, PLIS+ proves that combining contextual data and rules can lead to powerful personalized information services.