Presentation 2013/3/4
Developing a Transferring Method for Web-click Stream Prediction based on Sequential Pattern Evaluation Indices
Hidenao ABE,
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Abstract(in English) In this paper, a method for constructing transferable web-click stream prediction models based on sequential pattern evaluation indices is described. For predicting end points of click streams, the click streams are assumed as sequential data. Then, a sequential pattern generation method is applied to extract features of each click stream data. Based on these features, a classification learning algorithm is applied to construct click stream end point prediction models. In this study, evaluation indices for sequential pattern are introduced to abstract each click stream data for transferring constructed the predictive models. In the experiment, the method is applied to a benchmark click stream data to predict the end points. The result shows that the method can obtained more accurate predictive models with a decision tree learner and a classification rule learner. Subsequently, availability for transferring the predictive morels to different period is discussed.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Web-click Stream Prediction / Sequential Pattern Mining / Transfer Learning
Paper # AI2012-45
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Conference Information
Committee AI
Conference Date 2013/3/4(1days)
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Registration To Artificial Intelligence and Knowledge-Based Processing (AI)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Developing a Transferring Method for Web-click Stream Prediction based on Sequential Pattern Evaluation Indices
Sub Title (in English)
Keyword(1) Web-click Stream Prediction
Keyword(2) Sequential Pattern Mining
Keyword(3) Transfer Learning
1st Author's Name Hidenao ABE
1st Author's Affiliation Faculty of Information and Communications, Bunkyo University()
Date 2013/3/4
Paper # AI2012-45
Volume (vol) vol.112
Number (no) 477
Page pp.pp.-
#Pages 6
Date of Issue