Paper Info
Title
Discovering Point-of-Interest Signatures Based on Group Features from Geo-social Networking Data
Abstract
In recent years, location-based social networking services (LBSNSs) have become popular, generating a huge volume of geo-social networking data, such as check-in records and geo-tagged photos. The geo-social networking data provide a new source for discovering the real-world user behaviors. The information is useful for different applications, such as location prediction and point-of-interest (POI) recommendation. For LBSNSs, the research in POI recommendation have widely studied the user preferences over POIs and social influences between users. However, POIs are usually favored by or suitable for different kinds of groups, such as a small group, a tight group, or a close group. In this paper, we propose an approach to discovering POI signatures from geo-social networking data. For each POI, we first discover whether it has been visited by any groups of people and the features of these groups from user trajectories. We then generate the signature for each POI based on the discovered group features. We conduct experiments on the real data of the check-in records from Bright kite, and show the various kinds of POI signatures we found.
Year
DOI
Venue
2013
10.1109/.43
TAAI
Keywords
Field
DocType
geo-social networking data,check-in record,small group,group features,discovering point-of-interest,poi signature,close group,group feature,location-based social networking service,poi recommendation,tight group,geographic information systems
Social group,Geographic information system,World Wide Web,Social network,Computer science,Kite,Social influence,Point of interest,Location prediction
Conference
ISSN
Citations 
PageRank 
1066-6192
0
0.34
References 
Authors
8
5
Name
Order
Citations
PageRank
Ling-Yin Wei122714.05
Mi-Yen Yeh226825.85
Grace Lin300.34
Ya Hui Chan400.34
Wei Jung Lai500.34