Forecasting complex group behavior via multiple plan recognition
Li, Xiaochen; Mao, Wenji; Zeng, Daniel
Source PublicationFRONTIERS OF COMPUTER SCIENCE
2012-02-01
Volume6Issue:1Pages:102-110
SubtypeArticle
AbstractGroup behavior forecasting is an emergent research and application field in social computing. Most of the existing group behavior forecasting methods have heavily relied on structured data which is usually hard to obtain. To ease the heavy reliance on structured data, in this paper, we propose a computational approach based on the recognition of multiple plans/intentions underlying group behavior.We further conduct human experiment to empirically evaluate the effectiveness of our proposed approach.
KeywordGroup Behavior Forecasting Multiple Plan Recognition Graph Search
WOS HeadingsScience & Technology ; Technology
WOS KeywordMODEL
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods
WOS IDWOS:000299768800008
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/3611
Collection复杂系统管理与控制国家重点实验室_先进控制与自动化
AffiliationChinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
First Author AffilicationChinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Li, Xiaochen,Mao, Wenji,Zeng, Daniel. Forecasting complex group behavior via multiple plan recognition[J]. FRONTIERS OF COMPUTER SCIENCE,2012,6(1):102-110.
APA Li, Xiaochen,Mao, Wenji,&Zeng, Daniel.(2012).Forecasting complex group behavior via multiple plan recognition.FRONTIERS OF COMPUTER SCIENCE,6(1),102-110.
MLA Li, Xiaochen,et al."Forecasting complex group behavior via multiple plan recognition".FRONTIERS OF COMPUTER SCIENCE 6.1(2012):102-110.
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