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 dynamic 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.

Multi-agent architecture for point of interest detection and recommendation

Cavallaro Claudia;Verga Gabriella;Tramontana Emiliano;Muscato Orazio
2019

Abstract

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 dynamic 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.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11769/377368
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