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A Two-Stage Prediction Model for Web Page Transition
http://hdl.handle.net/2261/2470
http://hdl.handle.net/2261/2470f9b1b2f1-df39-41a3-8d6e-7c31fd3999e8
Item type | テクニカルレポート / Technical Report(1) | |||||
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公開日 | 2017-01-17 | |||||
タイトル | ||||||
タイトル | A Two-Stage Prediction Model for Web Page Transition | |||||
言語 | ||||||
言語 | eng | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | pate transition | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | prediction model | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | log file | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | statistical modeling | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Markov transition matrix | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | data mining | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_18gh | |||||
資源タイプ | technical report | |||||
アクセス権 | ||||||
アクセス権 | metadata only access | |||||
アクセス権URI | http://purl.org/coar/access_right/c_14cb | |||||
著者 |
Abe, Makoto
× Abe, Makoto |
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著者所属 | ||||||
値 | University of Tokyo | |||||
抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | Utilizing data from a log file, a two-stage model for step-ahead web page prediction that permits adaptive page customization in real-time is proposed. The first stage predicts the next page of a viewer based on a variant of a Markov transition matrix computed from page sequences of other visitors who read the same pages as that viewer did thus far. The second stage re-analyzes the incorrect exit/continuation predictions of the first stage through data mining, incorporating the visitor's viewing behavior observed from the log file. The two-stage process takes advantage of a robust, theory-driven nature of statistical modeling for extracting the overall feature of the data, and a flexible, data-driven nature of data mining to capture any idiosyncrasies and complications unresolved in the first stage. The empirical result with a test site implies that the first stage alone is sufficiently accurate (50.3%) in predicting page transitions. Prediction of site exit was even better with 100% of the exit and 90.8% of the continuation predictions being correct. The result was compared against other models for predictive accuracy. | |||||
内容記述 | ||||||
内容記述タイプ | Other | |||||
内容記述 | International Journal of Electronic Business. 掲載予定. | |||||
内容記述 | ||||||
内容記述タイプ | Other | |||||
内容記述 | 本文フィルはリンク先を参照のこと | |||||
書誌情報 |
Discussion paper series. CIRJE-F 巻 2003-CF-194, 発行日 2003-02 |
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書誌レコードID | ||||||
収録物識別子タイプ | NCID | |||||
収録物識別子 | AA11450569 | |||||
フォーマット | ||||||
内容記述タイプ | Other | |||||
内容記述 | application/pdf | |||||
日本十進分類法 | ||||||
主題Scheme | NDC | |||||
主題 | 330 | |||||
出版者 | ||||||
出版者 | 日本経済国際共同センター | |||||
出版者別名 | ||||||
値 | Center for International Research on the Japanese Economy | |||||
関係URI | ||||||
識別子タイプ | URI | |||||
関連識別子 | http://www.cirje.e.u-tokyo.ac.jp/research/dp/2003/2003cf194ab.html |