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IFSR 2005 >
このアイテムの引用には次の識別子を使用してください:
http://hdl.handle.net/10119/3892
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| タイトル: | Subscriber Number Forecasting Tool Based on Subscriber Attribute Distribution for Evaluating Improvement Strategies |
| 著者: | Hiramatsu, Ayako
Shono, Yuji
Oiso, Hiroaki
Komoda, Norihisa |
| キーワード: | simulation
modeling
customer retention |
| 発行日: | Nov-2005 |
| 出版者: | JAIST Press |
| 抄録: | In this paper, a subscriber number forecasting tool that evaluates quiz game mobile content improvement strategies is developed. Unsubscription rates depend on such subscriber attributes such as consecutive months, stages, rankings, and so on. In addition, content providers can anticipate change in unsubscription rates for each content improvement strategy. However, subscriber attributes change dynamically. Therefore, a method that deals with dynamic subscriber attribute changes is proposed. According to the features of content improvement strategies, content providers decide the conditions and the rates of unsubscription changes. Then the unsubscription rate for each segment is recalculated. In the period doing which a content improvement strategy has not been launched, prediction accuracy in the following there months of the proposed (subscriber-based) prediction method was compared with the segment-based prediction method. |
| 記述: | The original publication is available at JAIST Press http://www.jaist.ac.jp/library/jaist-press/index.html
IFSR 2005 : Proceedings of the First World Congress of the International Federation for Systems Research : The New Roles of Systems Sciences For a Knowledge-based Society : Nov. 14-17, 2102, Kobe, Japan
Symposium 3, Session 6 : Intelligent Information Technology and Applications Knowledge Management |
| 言語: | ENG |
| URI: | http://hdl.handle.net/10119/3892 |
| ISBN: | 4-903092-02-X |
| 出現コレクション: | IFSR 2005
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このアイテムのファイル:
| ファイル |
記述 |
サイズ | 形式 |
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| 20189.pdf | | 201Kb | Adobe PDF | 見る/開く |
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