Multi-Agent Architecture for Point of Interest Detection and Recommendation

Claudia Cavallaro, Gabriella Verga, Emiliano Tramontana, Orazio Muscato
2019 Workshop From Objects to Agents  
Geographical positions are widely employed in many applications, such as recommendation systems. The wide-spread use of mobile devices and location-based Internet services (e.g., Google Maps) gives the opportunity to collect user locations. Taking advantage of a multi-agent system, this work proposes an approach providing users with personalised recommendations of places of interests, such as libraries, museum, restaurants, etc. The approach offers a better experience by giving additional
more » ... c data (e.g. popularity, as number of users) to a list of Points Of Interest (POIs), and by exploring their temporal relations. Indeed, for POIs, which we determine using a DBSCAN algorithm, we take into account the time slots when the users visited them, to offer a more advanced service. Finally, the approach was designed to preserve the privacy of users, i.e. it does not reveal the position of users.
dblp:conf/woa/CavallaroVTM19 fatcat:qige62dbgzcrrccki6tskv2lsm