1、外文标题： Web Content Recommender System based on Consumer Behavior Modeling 外文作者： ACM Fong ， B Zhou ， SC Hui ， GY Hong ， TA Do 文献出处 : IEEE Transactions on Consumer Electronics , 2011 , 57 (2) :962-969 英文 1595 单词， 8495 字符，中文 2689 汉字。 此文档是外文翻译成品，无需调整复杂的格式哦！下载之后直接
2、可用，方 便快捷！只需二十多元。 Web Content Recommender System based on Consumer Behavior Modeling A. C. M. Fong, Senior Member, IEEE, Baoyao Zhou, S. C. Hui, Senior Member, IEEE,Guan Y. Hong, and The Anh Do Abstract Web surfing has become a popular activity for many consumers who not only make purchases onl
3、ine, but also seek relevant information on products and services before they commit to buy. The authors propose a web recommender that models user habits and behaviors by constructing a knowledge base using temporal web access patterns as input. Fuzzy logic is applied to represent real-life temporal
4、 concepts and requested resources of periodic pattern-based web access activities. The fuzzy representation is used to construct a knowledge base of the user's web access habits and behaviors, which is used to provide timely personalized recommendations to the user. The proposed approach is appl
5、icable to delivery of recommendations on consumers' portable devices because compute-intensive processing is performed offline and in advance. With the increasing availability and popularity of web- enabled consumer mobile devices, it is believed that the CE world of tomorrow will be increasingl
6、y web-oriented. Experiments conducted to evaluate the performance of the proposed approach have shown very good results1. Index Terms Consumer behavior modeling, personalization, web content recommender, consumer internet application. I. INTRODUCTION The web has become an increasingly popular medium for consumer to exchange or find ideas, opinions, experiences on products and services. Many consumers go further than online information sharing and actually perform purchases on the web. Increasing availability and popularity of porta
