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Abstract
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.
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University of Minnesota, 4-192 EE/CS Building, 200 Union Street SE, Minneapolis, MN 55455, USA
Amit Bose, Kalyan Beemanapalli & Jaideep Srivastava
Intel Corporation, FM1-56, 1900 Prairie City Road, Folsom, CA 95630, USA
Sigal Sahar
- Amit Bose
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- Kalyan Beemanapalli
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- Jaideep Srivastava
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- Sigal Sahar
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Bose, A., Beemanapalli, K., Srivastava, J., Sahar, S. (2007). Incorporating Concept Hierarchies into Usage Mining Based Recommendations. In: Nasraoui, O., Spiliopoulou, M., Srivastava, J., Mobasher, B., Masand, B. (eds) Advances in Web Mining and Web Usage Analysis. WebKDD 2006. Lecture Notes in Computer Science(), vol 4811. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77485-3_7
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