Gyözö Gidófalvi

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The efficient analysis of spatio–temporal data, generated by moving objects, is an essential requirement for intelligent location–based services. Spatio-temporal rules can be found by constructing spatio–temporal baskets, from which traditional association rule mining methods can discover spatio–temporal rules. When the items in the baskets are(More)
The popularity of embedded positioning technologies in mobile devices and the development of mobile communication technology have paved the way for powerful location-based services (LBSs). To make LBSs useful and user– friendly, heavy use is made of context information, including patterns in user location data which are extracted by data mining methods.(More)
Recent advances in communication and information technology , such as the increasing accuracy of GPS technology and the minia-turization of wireless communication devices pave the road for Location– Based Services (LBS). To achieve high quality for such services, spatio– temporal data mining techniques are needed. In this paper, we describe experiences with(More)
Recent technological trends enable modern traffic prediction and management systems in which the analysis and prediction of movements of objects is essential. To this extent the present paper proposes IncCCFR---a novel, incremental approach for managing, mining, and predicting the incrementally evolving trajectories of moving objects. In addition to reduced(More)
Transportation-related problems, like road congestion, parking, and pollution, are increasing in most cities. In order to reduce traffic, recent work has proposed methods for vehicle sharing, for example for sharing cabs by grouping "closeby" cab requests and thus minimizing transportation cost and utilizing cab space. However, the methods published so far(More)
Delivering 'relevant' advertisements to consumers carrying mobile devices is regarded by many as one of the most promising mobile business opportunities. The relevance of a mobile ad depends on at least two factors: (1) the proximity of the mobile consumer to the product or service being advertised, and (2) the match between the product or service and the(More)
In order to provide context--aware Location--Based Services, real location data of mobile users must be collected and analyzed by spatio--temporal data mining methods. However, the data mining methods need precise location data, while the mobile users want to protect their location privacy. To remedy this situation, this paper first formally defines novel(More)
Emerging trends in urban mobility have accelerated the need for effective traffic prediction and management systems. The present paper proposes a novel approach to using continuously streaming moving object trajectories for traffic prediction and management. The approach continuously performs three functions for streams of moving object positions in road(More)