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.
|Titolo:||Multi-agent architecture for point of interest detection and recommendation|
|Data di pubblicazione:||2019|
|Appare nelle tipologie:||4.1 Contributo in Atti di convegno|