Paper Info
Title
On socio-spatial group query for location-based social networks
Abstract
Challenges faced in organizing impromptu activities are the requirements of making timely invitations in accordance with the locations of candidate attendees and the social relationship among them. It is desirable to find a group of attendees close to a rally point and ensure that the selected attendees have a good social relationship to create a good atmosphere in the activity. Therefore, this paper proposes Socio-Spatial Group Query (SSGQ) to select a group of nearby attendees with tight social relation. Efficient processing of SSGQ is very challenging due to the tradeoff in the spatial and social domains. We show that the problem is NP-hard via a proof and design an efficient algorithm SSGSelect, which includes effective pruning techniques to reduce the running time for finding the optimal solution. We also propose a new index structure, Social R-Tree to further improve the efficiency. User study and experimental results demonstrate that SSGSelect significantly outperforms manual coordination in both solution quality and efficiency.
Year
DOI
Venue
2012
10.1145/2339530.2339679
KDD
Keywords
Field
DocType
good social relationship,good atmosphere,social domain,nearby attendees,socio-spatial group query,tight social relation,social relationship,efficient algorithm,selected attendees,candidate attendees,location-based social network,efficient processing,social networks,social network,social relation,spatial index
Social relation,Data mining,Social relationship,Social network,Computer science,Artificial intelligence,Impromptu,Machine learning
Conference
Citations 
PageRank 
References 
41
1.18
10
Authors
4
Name
Order
Citations
PageRank
De-Nian Yang158666.66
Chih-Ya Shen210317.13
Wang-Chien Lee35765346.32
Ming Chen465071277.71