Finding effective geo-social group for impromptu activities with diverse demands

Chen, Lu, Liu, Chengfei, Zhou, Rui, Xu, Jiajie, Yu, Jeffrey Xu and Li, Jianxin 2020, Finding effective geo-social group for impromptu activities with diverse demands, in KDD '20 : Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, Association for Computing Machinery (ACM), New York, N.Y., pp. 698-708, doi: 10.1145/3394486.3403114.

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Title Finding effective geo-social group for impromptu activities with diverse demands
Author(s) Chen, Lu
Liu, Chengfei
Zhou, Rui
Xu, Jiajie
Yu, Jeffrey Xu
Li, JianxinORCID iD for Li, Jianxin orcid.org/0000-0002-9059-330X
Conference name KDD '20 Knowledge Discovery and Data Mining. International Conference (2020 : 26th : Virtual Event, USA)
Conference location Virtual Event, USA
Conference dates 23 - 27 Aug. 2020
Title of proceedings KDD '20 : Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
Publication date 2020
Start page 698
End page 708
Total pages 11
Publisher Association for Computing Machinery (ACM)
Place of publication New York, N.Y.
Keyword(s) geo-social group
truss
attributed graph
CORE2020 A*
ISBN 9781450379984
Language eng
DOI 10.1145/3394486.3403114
Indigenous content off
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2020, The Authors
Persistent URL http://hdl.handle.net/10536/DRO/DU:30141150

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