政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/27079

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政大機構典藏 > 商學院 > 資訊管理學系 > 期刊論文 > Item 140.119/27079

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/27079

Title:	A Preference Scoring Technique for Personalized Advertisements on Internet Storefronts
Authors:	Kim,J. W.;Lee H.;M. J. Shaw;張欣綠;M. Nelson Chang, Hsin-Lu
Keywords:	Internet storefront;Customization;Personalization;Recommendation techniques;Electronic commerce
Date:	2006-02
Issue Date:	2009-01-17 16:08:29 (UTC+8)
Abstract:	This paper describes a new personalized advertisement selection technique based on a customer’s preference scores for product categories. This method performs well, despite having low data and analysis requirements, relative to other methods in use. Customer preference scores are updated based on a customer’s initial profile, purchase history, and behavior in an Internet storefront, and are then used to select and display appropriate advertisements on Internet web pages when the customer visits the Internet storefront. Compared with currently available recommendation techniques such as collaborative filtering or rule-based methods, preference scoring techniques use only a single customer’s data to select appropriate advertisements and do not require a learning data set, and yet have competitive performance and can reflect changes in a customers’ preference. An experiment is performed to compare two alternative data storage structures, the preference table and the preference tree, with random selection and collaborative filtering.
Relation:	Mthematical and Computer Modelling, 44(1/2), 3-15
Data Type:	article
DOI 連結:	http://dx.doi.org/10.1016/j.mcm.2004.12.011
DOI:	10.1016/j.mcm.2004.12.011
Appears in Collections:	[資訊管理學系] 期刊論文

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