A personalized recommendation system based on product taxonomy for one-to-one marketing online

被引：70

作者：

Hung, LP ^{[1
]}

机构：

[1] No Taiwan Inst Sci & Technol, Dept Informat Management, Taipei 112, Taiwan

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2005年 / 29卷 / 02期

关键词：

personalized recommendation system; one-to-one marketing; product taxonomy; customer classification;

D O I：

10.1016/j.eswa.2005.04.016

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Nowadays, Electronic Commerce (EC) provides a new gateway for customers shopping online. One of the most significant advantages offered by online shops is convenience. Online shopping is no longer a time-consuming task and, in fact, is an energy-saving activity. Therefore, shortening customers' product searching time is the key to an online shop's success. In order to serve customers instantly and efficiently, it is essential to recognize each customer's unique and particular needs and recommend a personalized shopping list. In this paper, we construct a recommendation system based on a modified product taxonomy and customer classification to identify customers' shopping behavior: product addictive, brand addictive or a hybrid addictive. By analyzing each customer's preferred brand or product, our proposed system can recommend products to customers either at the general or at the specific levels. (C) 2005 Elsevier Ltd. All rights reserved.

引用

页码：383 / 392

页数：10

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