Exploring IoT Location Information to Perform Point of Interest Recommendation Engine: Traveling to a New Geographical Region

Sensors
Xu YangXiaoya Chen

Abstract

With the development of wireless Internet and the popularity of location sensors in mobile phones, the coupling degree between social networks and location sensor information is increasing. Many studies in the Location-Based Social Network (LBSN) domain have begun to use social media and location sensing information to implement personalized Points-of-interests (POI) recommendations. However, this approach may fall short when a user moves to a new district or city where they have little or no activity history and social network friend information. Thus, a need to reconsider how we model the factors influencing a user's preferences in new geographical regions in order to make personalized and relevant recommendation. A POI in LBSNs is semantically enriched with annotations such as place categories, tags, tips or user reviews which implies knowledge about the nature of the place as well as a visiting person's interests. This provides us with opportunities to better understand the patterns in users' interests and activities by exploiting the annotations which will continue to be useful even when a user moves to unfamiliar places. In this research, we proposed a location-aware POI recommendation system that models user preferences ...Continue Reading

Software Mentioned

librec1
java
SVD
Yelp
NRLRS
CKNN
Foursquare

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