Forecasting complex group behavior via multiple plan recognition

Xiaochen Li, Wenji Mao, Daniel Zeng

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Group 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.

Original languageEnglish (US)
Pages (from-to)102-110
Number of pages9
JournalFrontiers of Computer Science in China
Volume6
Issue number1
DOIs
StatePublished - Feb 1 2012

    Fingerprint

Keywords

  • graph search
  • group behavior forecasting
  • multiple plan recognition

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this