Presentation 2003/1/17
Action Prediction for a User Using Inductive Learning with N-gram
Jin'an XU, Kenji ARAKI, Koji TOCHINAI,
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Abstract(in English) We have proposed a method to predict a user action using Inductive Learning with N-gram. This method acquires rules from the state history automatically by its learning capability, and the acquired rules express the user's habit and tastes. Therefore the system is able to adapt dynamically to each user. The user must proofread the errors of prediction results.However, the erroneous conversion decreases by the system's dynamic adaptation. This paper unified N-gram and Inductive Learning which built the new Point-Line Based Perdiction system. The high prediction accuracy of the experiment were gotten and better dynamic adaptation capability was also shown.
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Keyword(in English) Inductive Learning / N-gram / Action Prediction / Adaptability / Point-line Based Prediction
Paper # HIP2002-61
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Committee HIP
Conference Date 2003/1/17(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Action Prediction for a User Using Inductive Learning with N-gram
Sub Title (in English)
Keyword(1) Inductive Learning
Keyword(2) N-gram
Keyword(3) Action Prediction
Keyword(4) Adaptability
Keyword(5) Point-line Based Prediction
1st Author's Name Jin'an XU
1st Author's Affiliation Graduate School of Engineering, Hokkaido University()
2nd Author's Name Kenji ARAKI
2nd Author's Affiliation Graduate School of Engineering, Hokkaido University
3rd Author's Name Koji TOCHINAI
3rd Author's Affiliation Graduate School of Business Administration, Hokkai-Gakuen University
Date 2003/1/17
Paper # HIP2002-61
Volume (vol) vol.102
Number (no) 595
Page pp.pp.-
#Pages 8
Date of Issue