博碩士論文 etd-0813104-175738 詳細資訊


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姓名 蔡嘉文(Chai-wen Tsai) 電子郵件信箱 m9142639@student.nsysu.edu.tw
畢業系所 資訊管理學系研究所(Information Management)
畢業學位 碩士(Master) 畢業時期 92學年第2學期
論文名稱(中) 運用GP關聯法則來做目標行銷
論文名稱(英) Targeted Advertising Based on GP-association rules
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    摘要(中) 針對特定群體之需求擬定產品及行銷策略長久以來為企業所重視,為了達到更有效率的市場區隔,本研究提出一個新的方法來推薦產品。剛開始先從交易紀錄資料中找出顧客屬性與產品類別經常一起時出現的關聯法則,其中顧客屬性與產品類別都包含了階層的概念。然後根據之前找到的關聯法則,在給定推薦產品情況下,利用演算法來找出目標顧客。方法評估上,先從校內圖書館的OPAC System 取得讀者的借閱紀錄資料,藉由調整不同參數分別衡量預測的正確性與目標行銷的有效性,結果顯示跟其他方法相比,可以達到較高的預測的正確性與推薦有效性。
    摘要(英) Targeting a small portion of customers for advertising has long been recognized by businesses. In this thesis we proposed a novel approach to promoting products with no prior transaction records. This approach starts with discovering the GP-association rules between customer types and product genres that had occurred frequently in transaction records. Customers are characterized by demographic attributes, some of these attributes have concept hierarchies and products can be generalized through some product taxonomy. Based on GP-association rules set, we developed a comprehensive algorithm to locating a short list of prospective customers for a given promotion product. The new approach was evaluated using the patron’s circulation data from OPAC system of our university library. We measured the accuracy of estimated method and the effectiveness of targeted advertising in different parameters. The result shows that our approach achieved higher accuracy and effectiveness than other methods.
    關鍵字(中)
  • 目標行銷
  • GP關聯法則
  • 階層概念
  • 產品推薦
  • 關鍵字(英)
  • GP-association rules
  • Targeted Advertising
  • Product Recommendation
  • Concept Hierarchies
  • 論文目次 Table of Content
    Chapter 1 Introduction 1
    1.1 Research Background 1
    1.2 Research Motivations and Objectives 3
    1.3 Thesis Organization 6
    Chapter 2 Literature review 7
    2.1 GP-association rules 7
    2.1.1 Extended transaction 7
    2.1.2 GP-Apriori algorithm 9
    2.2 Estimating specialized rules from generalized rules 12
    2.3 Scheduling of web advertisements 15
    2.4 Optimized Association Rules 17
    Chapter 3 Targeted Advertising 21
    3.1 Problem Statement 21
    3.2 Value estimation 22
    3.3 Identifying applicable demographics of a GP-association rule 25
    3.4 Identifying disjoint demographic segments 28
    Chapter 4 Identifying Targeted Customers 30
    Chapter 5 Performance evaluations 33
    5.1 Accuracy of estimated confidence 34
    5.2 Effectiveness for targeted advertising 38
    Chapter 6 Conclusions 42
    References 43
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    [SPAM03] Spam laws, see http://www.spamlaws.com/.
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    口試委員
  • 魏志平 - 召集委員
  • 林福仁 - 委員
  • 黃三益 - 指導教授
  • 口試日期 2004-07-26 繳交日期 2004-08-13

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