Intelligent Techniques for Web Personalization and Recommender Systems in E-Commerce
Papers from the AAAI Workshop
Bamshad Mobasher, Sarabjot Singh Anand, Alfred Kobsa, and Dietmar Jannach, Cochairs
The web is now an integral part of numerous applications in which a user interacts with a company, government, employer, or an information provider. However, the potential of the web is hampered by the enormity of the content available and the diverse expectations of its user base. These challenges, in turn, have driven the increasing need to more intelligent, personalized, and adaptive web services or applications, such as e-commerce recommender systems. Businesses have come to realize the potential of these personalized and adaptive systems in order to increase sales and to retain customers. Likewise, Web users have come to rely on such systems to help them in more efficiently finding items of interest in large information spaces. The two AAAI 2007 workshops, the Fifth Workshop on Intelligent Techniques for Web Personalization (ITWP'07) and the Workshop on Recommender Systems in E-Commerce, joined forces to address a host of issues and challenges in the design, implementation, deployment, and evaluation of web personalization and recommendation solutions, both from a research as well as from a practical perspective. The topics covered by the two workshops included user or customer behavior modeling, preference elicitation, scalable and effective recommendation algorithms, personalized search and information access, data mining and web mining for personalization, trust and security in recommender systems, the use of semantics and ontologies in recommendation and web personalization, and the evaluation of recommender systems. The papers in these proceedings reflect the joint program of the two workshops. They were selected based on their quality and coverage, after a careful and rigorous review process by the internationally renowned program committees of the two workshops.