Web content recommender system based on consumer behavior modeling

Fong, A.C.M., Zhou, B., Hui, S.C., Hong, G. and Do, T.A. (2011) Web content recommender system based on consumer behavior modeling. IEEE Transactions on Consumer Electronics, 57(2), pp. 962-969. (doi: 10.1109/TCE.2011.5955246)

Full text not currently available from Enlighten.

Abstract

Web surfing has become a popular activity for many consumers who not only make purchases online, 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 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 applicable 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 webenabled consumer mobile devices, it is believed that the CE world of tomorrow will be increasingly web-oriented. Experiments conducted to evaluate the performance of the proposed approach have shown very good results.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Fong, Dr Alvis Cheuk Min
Authors: Fong, A.C.M., Zhou, B., Hui, S.C., Hong, G., and Do, T.A.
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
College/School:College of Science and Engineering > School of Computing Science
Journal Name:IEEE Transactions on Consumer Electronics
ISSN:0098-3063
ISSN (Online):1558-4127

University Staff: Request a correction | Enlighten Editors: Update this record