Mission-Based Navigational Behaviour Modeling for Web Recommender Systems

Web recommender systems anticipate the information needs of on-line users and provide them with recommendations to facilitate and personalize their navigation. There are many approaches to building such systems. Among them, using web access logs to generate users' navigational models capable of building a web recommender system is a popular approach, given its non-intrusiveness. However, using only one information channel, namely the web access history, is often insufficient for accurate recommendation prediction. We therefore advocate the use of additional available information channels, such as the content of visited pages and the connectivity between web resources, to better model user navigational behavior. This helps in better modeling users' concurrent information needs. In this chapter, we investigate a novel hybrid web recommender system, which combines access history and the content of visited pages, as well as the connectivity between web resources in a web site, to...

• Type: Conference
• Year: 2004
• Where: KDD
• Authors: Osmar R. Zaïane, Jia Li, Robert Hayward
• Keywords: Data Mining, Hybrid Web Recommender, KDD 2004, Web Access Logs, Web Recommender Systems