National Changhua University of Education Institutional Repository : Item 987654321/15882
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题名: Discovering Generalized Profile-Association Rules for the Targeted Advertising of New Products
作者: Hwang, San-Yih;Yang, Wan-Shiou
贡献者: 資訊管理學系
关键词: Data mining;Profile-association rules;Generalized profile-association rules;Fractional 0–1 knapsack problem;Greedy algorithms;Targeted advertising;Recommender systems
日期: 2008
上传时间: 2013-03-27T06:47:52Z
出版者: INFORMS
摘要: We propose a data-mining approach for the targeted marketing of new products that have never been rated or purchased by customers. This approach uncovers associations between customer types and product genres that frequently occurred in previous transaction records. Customer types are defined in terms of demographic attribute values that can be aggregated through concept hierarchies; product types can be generalized through product taxonomies. We use generalized profile-association rules (GP association rules) to identify the advertising targets for a given new product. In addition, we propose two algorithms—GP-Apriori and Merge-prune—to mine GP association rules and develop a value-based targeted advertising algorithm to select prospective customers of a new product on the basis of the discovered rules. We evaluate the proposed approach using both synthetic data and library-circulation data.
關聯: INFORMS Journal on Computing, 20(1): 34-45
显示于类别:[資訊管理學系所] 期刊論文

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