Take a look at the new version of this page: [ beta version ]. Tell us what you think.

ABSTRACT

Recommender systems do not always generate good recommendations for users. In order to improve recommender quality, we argue that recommenders need a deeper understanding of users and their information seeking tasks. Human-Recommender Interaction (HRI) provides a framework and a methodology for understanding users, their tasks, and recommender algorithms using a common language. Further, by using an analytic process model, HRI becomes not only descriptive, but also constructive. It can help with the design and structure of a recommender system, and it can act as a bridge between user information seeking tasks and recommender algorithms.

REFERENCES

• 1: Case, D.O. Looking for Information: A Survey of Research on Information Seeking, Needs, and Behavior. Academic Press: San Diego, CA, 2002.
• 2: JoAnn T. Hackos , Janice C. Redish, User and task analysis for interface design, John Wiley & Sons, Inc., New York, NY, 1998
• 3: Jonathan L. Herlocker , Joseph A. Konstan , Loren G. Terveen , John T. Riedl, Evaluating collaborative filtering recommender systems, ACM Transactions on Information Systems (TOIS), v.22 n.1, p.5-53, January 2004 [doi>10.1145/963770.963772]
• 4: Im, I., Hars, A. Finding Information Just For You: Knowledge Reuse Using Collaborative Filtering Systems. In Proc. of ICIS 2001, Association for Information Systems (2001), 349--360.
• 5: Sean M. McNee , Istvan Albert , Dan Cosley , Prateep Gopalkrishnan , Shyong K. Lam , Al Mamunur Rashid , Joseph A. Konstan , John Riedl, On the recommending of citations for research papers, Proceedings of the 2002 ACM conference on Computer supported cooperative work, November 16-20, 2002, New Orleans, Louisiana, USA [doi>10.1145/587078.587096]
• 6: Roberto Torres , Sean M. McNee , Mara Abel , Joseph A. Konstan , John Riedl, Enhancing digital libraries with TechLens+, Proceedings of the 4th ACM/IEEE-CS joint conference on Digital libraries, June 07-11, 2004, Tuscon, AZ, USA [doi>10.1145/996350.996402]
• 7: Zaslow, J. "If TiVo Thinks You Are Gay, Here's How To Set It Straight -- Amazon.com Knows You, Too, Based on What You Buy; Why All the Cartoons?" The Wall Street Journal, sect. A, p. 1, November 26, 2002.
• 8: Cai-Nicolas Ziegler , Sean M. McNee , Joseph A. Konstan , Georg Lausen, Improving recommendation lists through topic diversification, Proceedings of the 14th international conference on World Wide Web, May 10-14, 2005, Chiba, Japan [doi>10.1145/1060745.1060754]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Information filtering

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Retrieval models; Search process

Keywords:
collaborative filtering, human-recommender interaction, information seeking, personalization, recommender systems, user-centered design