Performance evaluation of classification methods in cultural modeling

Li Xiaochen, Mao Wenji, Daniel Zeng, Su Peng, Fei Yue Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Cultural modeling is an emergent and promising research area in social computing. It aims to develop behavioral models of groups and analyze the impact of culture factors on group behavior using computational methods. Classification methods play a critical role in cultural modeling domain. As various cultural-related datasets possess different properties, for group behavior prediction, it is important to gain a computational understanding of the performance of various classification methods. In this paper, we investigate the performance of seven representative classification algorithms using a benchmark cultural modeling dataset and analyze the experimental results.

Original languageEnglish (US)
Title of host publication2009 IEEE International Conference on Intelligence and Security Informatics, ISI 2009
Pages248-250
Number of pages3
DOIs
StatePublished - 2009
Event2009 IEEE International Conference on Intelligence and Security Informatics, ISI 2009 - Dallas, TX, United States
Duration: Jun 8 2009Jun 11 2009

Publication series

Name2009 IEEE International Conference on Intelligence and Security Informatics, ISI 2009

Other

Other2009 IEEE International Conference on Intelligence and Security Informatics, ISI 2009
CountryUnited States
CityDallas, TX
Period6/8/096/11/09

Keywords

  • Classification
  • Cultural modeling
  • Group behavior prediction

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems
  • Software

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