AAAI Publications, Twenty-Ninth AAAI Conference on Artificial Intelligence

Font Size: 
Content-Aware Point of Interest Recommendation on Location-Based Social Networks
Huiji Gao, Jiliang Tang, Xia Hu, Huan Liu

Last modified: 2015-02-18

Abstract


The rapid urban expansion has greatly extended the physical boundary of users' living area and developed a large number of POIs (points of interest). POI recommendation is a task that facilitates users' urban exploration and helps them filter uninteresting POIs for decision making. While existing work of POI recommendation on location-based social networks (LBSNs) discovers the spatial, temporal, and social patterns of user check-in behavior, the use of content information has not been systematically studied. The various types of content information available on LBSNs could be related to different aspects of a user's check-in action, providing a unique opportunity for POI recommendation. In this work, we study the content information on LBSNs w.r.t. POI properties, user interests, and sentiment indications. We model the three types of information under a unified POI recommendation framework with the consideration of their relationship to check-in actions. The experimental results exhibit the significance of content information in explaining user behavior, and demonstrate its power to improve POI recommendation performance on LBSNs.

Keywords


POI Recommendation; Location-based Social Networks; Content Aware

Full Text: PDF