Combination of Web page recommender systems


EXPERT SYSTEMS WITH APPLICATIONS, vol.37, no.4, pp.2911-2922, 2010 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 37 Issue: 4
  • Publication Date: 2010
  • Doi Number: 10.1016/j.eswa.2009.09.046
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.2911-2922
  • Istanbul Technical University Affiliated: No


With the rapid growth of the World Wide Web (www), finding useful information from the Internet has become a critical issue. Web recommender systems help users make decisions in this complex information space where the volume of information available to them is huge. Recently, a number of Web page recommender systems have been developed to extract the user behavior from the user's navigational path and predict the next request as s/he visits Web pages. However, each of these systems has its own merits and limitations. In this paper, we investigate a hybrid recommender system, which combines the results of several recommender techniques based on Web usage mining. We conduct a detailed comparative evaluation of how different combined methods and different recommendation techniques affect the prediction accuracy of the hybrid recommender. We then discuss the results in terms of using a hybrid recommender system instead of a single recommender model. Our results suggest that the hybrid recommender system is better in predicting the next request of a Web user. (C) 2009 Elsevier Ltd. All rights reserved.