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Social interaction mining in small group discussion using a smart meeting system

  • Zhiwen Yu
  • , Xingshe Zhou
  • , Zhiyong Yu
  • , Christian Becker
  • , Yuichi Nakamura
  • Northwestern Polytechnical University Xian
  • Fuzhou University
  • University of Mannheim
  • Kyoto University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, we propose a mining method to discover high-level semantic knowledge about human social interactions in small group discussion, such as frequent interaction patterns, the role of an individual (e.g., the "centrality" or "power"), subgroup interactions (e.g., two persons often interact with each other), and hot sessions. A smart meeting system is developed for capturing and recognizing social interactions. Interaction network in a discussion session is represented as a graph. Interaction graph mining algorithms are designed to analyze the structure of the networks and extract social interaction patterns. Preliminary results show that we can extract several interesting patterns that are useful for interpretation of human behavior in small group discussion.

Original languageEnglish
Title of host publicationUbiquitous Intelligence and Computing - 8th International Conference, UIC 2011, Proceedings
Pages40-51
Number of pages12
DOIs
StatePublished - 2011
Event8th International Conference on Ubiquitous Intelligence and Computing, UIC 2011 - Banff, AB, Canada
Duration: 2 Sep 20114 Sep 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6905 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Conference on Ubiquitous Intelligence and Computing, UIC 2011
Country/TerritoryCanada
CityBanff, AB
Period2/09/114/09/11

Keywords

  • graph mining
  • interaction mining
  • smart meeting
  • social interaction

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