Intelligent Techniques for Web Personalization

Cooperative Query Rewriting for Decision Making Support and Recommender Systems

“…Many recommendation techniques have been proposed to automate this mapping (Adomavicius and Tuzhilin 2005;Anand and Mobasher 2005;Burke 2002b) and there are many deployed recommender systems for CD, movies, music, and travel recommendation (MovieLens 2007;Linden et al 2003;Ricci et al 2006a). The most popular approach is called collaborative filtering, which recommends products to a user based on his commonalities (e.g., product rates) with other users (Resnick et al 1994;Shardanand and Maes 1995;Breese et al 1998;Sarwar et al 2001).…”

“…But search engines are keyword-based and are not much useful within a Web site to help the user to identify his preferred product in a catalogue. For this specific purpose, recommender systems, a new kind of information search and filtering technology, have been proposed (Resnick et al 1994;Shardanand and Maes 1995;Resnick and Varian 1997;Schafer et al 2001;Adomavicius and Tuzhilin 2005;Anand and Mobasher 2005). Recommender systems support personalized search, i.e., they help users to select products when large catalogues are available and the user does not have enough knowledge to select autonomously the best option.…”

“…But that assumption is not acceptable in eCommerce applications and in recommender systems where the user may not be interested in the additional product features proposed by the system (Anand and Mobasher 2005;Adomavicius and Tuzhilin 2005;Bridge et al 2006). Therefore, in a second evaluation, we assigned to each feature an acceptance probability proportional to the feature popularity, measured in real user interactions with the system.…”

Web Mining for the Integration of Data Mining with Business Intelligence in Web-Based Decision Support Systems

“…• Web Personalization/Recommendation: The user navigation behavior can be used to personalize web pages by making dynamic recommendations (e.g., pages, services, etc) for each web user (Anand, & Mobasher, 2003); • Categorization/Clustering of Content: Content data can be used to categorize/ cluster web pages into topic directories (Chakrabarti, 2000);…”

Proposal of a trust and reputation model to provide recommendation in open quality oriented environments

“…RSs appeared to help users to cope with the overwhelming amount and variety of information available on the Web and the rapid introduction of new e-business services (Ricci et al 2011). The study of recommender systems and recommendation techniques started in mid1990s (Goldberg et al 1992;Anand & Mobasher 2005;Mahmood & Ricci 2009;McSherry & Mironov 2009) and in recent years it has become an important research area with thousands of publications; dedicated conferences and workshops (such as ACM Recommender Systems, RecSys); RSs courses at institutions of higher education; books and special issues at academic journals (such as AI Communications, IEEE Intelligent Systems or ACM Transactions on Computer-Human Interaction). Moreover, many authors have published extensive reviews on the field (Frias-Martinez et al 2006;Burke 2007;Frias-Martinez et al 2009;Kim et al 2010;Park et al 2012;Sezgin & Ozkan 2013;Lu et al 2015).…”