Incorporating Concept Hierarchies into Usage Mining Based Recommendations

• Published in: Advances in Web Mining and Web Usage Analysis Vol. 4811; pp. 110 - 126
• Main Authors: Bose, Amit, Beemanapalli, Kalyan, Srivastava, Jaideep, Sahar, Sigal
• Format: Book Chapter
• Language: English
• Published: Germany Springer Berlin / Heidelberg 2007; Springer Berlin Heidelberg
• Series: Lecture Notes in Computer Science
• Subjects: Alignment Score; Artificial intelligence; Domain Knowledge; Network hardware; Recommender System; Usage Mining; User Session
• ISBN: 354077484X; 9783540774846
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-540-77485-3_7

Recent studies have shown that conceptual and structural characteristics of a website can play an important role in the quality of recommendations provided by a recommendation system. Resources like Google Directory, Yahoo! Directory and web-content management systems attempt to organize content conceptually. Most recommendation models are limited in their ability to use this domain knowledge. We propose a novel technique to incorporate the conceptual characteristics of a website into a usage-based recommendation model. We use a framework based on biological sequence alignment. Similarity scores play a crucial role in such a construction and we introduce a scoring system that is generated from the website’s concept hierarchy. These scores fit seamlessly with other quantities used in similarity calculation like browsing order and time spent on a page. Additionally they demonstrate a simple, extensible system for assimilating more domain knowledge. We provide experimental results to illustrate the benefits of using concept hierarchy.