Performance evaluation of machine learning methods in cultural modeling

Xiao Chen Li, Wen Ji Mao, Dajun Zeng, Peng Su, Fei Yue Wang

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Cultural modeling (CM) is an emergent and promising research area in social computing. It aims to develop behavioral models of human groups and analyze the impact of culture factors on human group behavior using computational methods. Machine learning methods, in particular classification, play a critical role in such applications. Since various cultural-related data sets possess different characteristics, it is important to gain a computational understanding of performance characteristics of various machine learning methods. In this paper, we investigate the performance of seven representative classification algorithms using a benchmark cultural modeling data set and analyze the experimental results as to group behavior forecasting.

Original languageEnglish (US)
Pages (from-to)1010-1017
Number of pages8
JournalJournal of Computer Science and Technology
Volume24
Issue number6
DOIs
StatePublished - Nov 2009

Fingerprint

Performance Evaluation
Learning systems
Machine Learning
Computational methods
Modeling
Social Computing
Data structures
Data Modeling
Classification Algorithm
Computational Methods
Forecasting
Benchmark
Experimental Results
Human
Model
Culture

Keywords

  • Classification
  • Cultural modeling (CM)
  • Group behavior forecasting
  • Machine learning

ASJC Scopus subject areas

  • Hardware and Architecture
  • Software
  • Computational Theory and Mathematics
  • Theoretical Computer Science
  • Computer Science Applications

Cite this

Performance evaluation of machine learning methods in cultural modeling. / Li, Xiao Chen; Mao, Wen Ji; Zeng, Dajun; Su, Peng; Wang, Fei Yue.

In: Journal of Computer Science and Technology, Vol. 24, No. 6, 11.2009, p. 1010-1017.

Research output: Contribution to journalArticle

Li, Xiao Chen ; Mao, Wen Ji ; Zeng, Dajun ; Su, Peng ; Wang, Fei Yue. / Performance evaluation of machine learning methods in cultural modeling. In: Journal of Computer Science and Technology. 2009 ; Vol. 24, No. 6. pp. 1010-1017.
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