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JACIII Vol.12 No.2 pp. 150-155
doi: 10.20965/jaciii.2008.p0150
(2008)

Paper:

Haar Wavelets for Online-Game Player Classification with Dynamic Time Warping

Ruck Thawonmas and Keita Iizuka

Intelligent Computer Entertainment Laboratory, Graduate School of Science and Engineering, Ritsumeikan University, 1-1-1 Nojihigashi, Kusatsu, Shiga 525-8577, Japan

Received:
May 14, 2007
Accepted:
September 12, 2007
Published:
March 20, 2008
Keywords:
online game, player classification, wavelet transform, dynamic time warping, action sequences
Abstract

Online game players’ action sequences, while important to understand their behavior, usually contain noise and/or redundancy, making them unnecessarily long. To acquire briefer sequences representative of players’ features, we apply the Haar wavelet transform to action sequences and reconstruct them from selected wavelet coefficients. Results indicate that this approach is effective in classification when the k-nearest neighbor classifier is used to classify players based on dynamic time warping distances between reconstructed sequences.

Cite this article as:
Ruck Thawonmas and Keita Iizuka, “Haar Wavelets for Online-Game Player Classification with Dynamic Time Warping,” J. Adv. Comput. Intell. Intell. Inform., Vol.12, No.2, pp. 150-155, 2008.
Data files:
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