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International Workshop on Knowledge Discovery on the Web

WebKDD 2005: Advances in Web Mining and Web Usage Analysis pp 77–95Cite as

USER: User-Sensitive Expert Recommendations for Knowledge-Dense Environments

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4198))

Abstract

Traditional recommender systems tend to focus on e-commerce applications, recommending products to users from a large catalog of available items. The goal has been to increase sales by tapping into the user’s interests by utilizing information from various data sources to make relevant recommendations. Education, government, and policy websites face parallel challenges, except the product is information and their users may not be aware of what is relevant and what isn’t. Given a large, knowledge-dense website and a nonexpert user searching for information, making relevant recommendations becomes a significant challenge. This paper addresses the problem of providing recommendations to non-experts, helping them understand what they need to know, as opposed to what is popular among other users. The approach is usersensitive in that it adopts a ‘model of learning’ whereby the user’s context is dynamically interpreted as they browse and then leveraging that information to improve our recommendations.

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Author information

Authors and Affiliations

  1. College of Liberal Arts, University of Minnesota, 101 Pleasant St. SE, 55455, Minneapolis, MN, United States of America

    Colin DeLong

  2. Department of Computer Science, University of Minnesota, 200 Union Street SE, 55455, Minneapolis, MN, United States of America

    Prasanna Desikan & Jaideep Srivastava

Authors
  1. Colin DeLong
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  2. Prasanna Desikan
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  3. Jaideep Srivastava
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Editor information

Editors and Affiliations

  1. Knowledge Discovery & Web Mining Lab, University of Louisville, 40292, Louisville, KY, USA

    Olfa Nasraoui

  2. University of Alberta, Canada

    Osmar Zaïane

  3. Faculty of Computer Science, Otto-von-Guericke-University Magdeburg, Germany

    Myra Spiliopoulou

  4. Center for Web Intelligence School of Computing, DePaul University, Chicago, Illinois, USA

    Bamshad Mobasher

  5. Data Miners Inc., 77 North Washington Street, 02114, Boston, MA, USA

    Brij Masand

  6. University of Illinois, Chicago, IL, USA

    Philip S. Yu

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© 2006 Springer-Verlag Berlin Heidelberg

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DeLong, C., Desikan, P., Srivastava, J. (2006). USER: User-Sensitive Expert Recommendations for Knowledge-Dense Environments. In: Nasraoui, O., Zaïane, O., Spiliopoulou, M., Mobasher, B., Masand, B., Yu, P.S. (eds) Advances in Web Mining and Web Usage Analysis. WebKDD 2005. Lecture Notes in Computer Science(), vol 4198. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11891321_5

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  • DOI: https://doi.org/10.1007/11891321_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46346-7

  • Online ISBN: 978-3-540-46348-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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