On socio-spatial group query for location-based social networks

Authors:
De-Nian Yang;Chih-Ya Shen;Wang-Chien Lee;Ming-Syan Chen
Affiliations:
Academia Sinica, Taipei, Taiwan Roc;National Taiwan University, Taipei, Taiwan Roc;The Penn State University, State College, PA, USA;National Taiwan University, Taipei, Taiwan Roc
Venue:
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Year:
2012

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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.