Content area

Abstract

The geo-social group query is to find a group of users for the query point based on location and social information. In this paper, we propose the range constrained group query (RCGQ) on attribute social graph, considering social information, spatial information, keyword information and user group size. We prove that RCGQ problem is NP-hard. For the query, we propose four methods, namely the combination-based group expansion method (COM), the single–multi group expansion method (S–M), the single–single group expansion method (S–S) and the multi–multi group expansion method (M–M). The first method is based on combination. The last three methods are based on social relations. COM uses combination to find user groups. The social relations are not used in the combinatorial process. S–M, S–S and M–M use the social relations to find user groups. Pruning strategies are proposed for the four methods. Finally, experiments demonstrate the efficiency of the proposed methods.

Details

Business indexing term
Title
Range constrained group query on attribute social graph
Author
Chen, Zijun 1 ; Shao, Wenwen 1 ; Liu, Wenyuan 1 

 Yanshan University, School of Information Science and Engineering, Qinhuangdao, China (GRID:grid.413012.5) (ISNI:0000 0000 8954 0417); The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province, Qinhuangdao, China (GRID:grid.413012.5) 
Publication title
Volume
42
Issue
3
Pages
337-375
Publication year
2024
Publication date
Sep 2024
Publisher
Springer Nature B.V.
Place of publication
New York
Country of publication
Netherlands
ISSN
09268782
e-ISSN
15737578
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2024-03-30
Milestone dates
2024-01-13 (Registration); 2024-01-13 (Accepted)
Publication history
 
 
   First posting date
30 Mar 2024
ProQuest document ID
3255420270
Document URL
https://www.proquest.com/scholarly-journals/range-constrained-group-query-on-attribute-social/docview/3255420270/se-2?accountid=208611
Copyright
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
Last updated
2025-09-29
Database
ProQuest One Academic