Talking the talk vs. walking the walk: salience of information needs in querying vs. browsing

ABSTRACT

Traditional information retrieval models assume that users express their information needs via text queries (i.e., their "talk"). In this poster, we consider Web browsing behavior outside of interactions with retrieval systems (i.e., users' "walk") as an alternative source of signal describing users' information needs, and compare it to the query-expressed information needs on a large dataset. Our findings demonstrate that information needs expressed in different behavior modalities are largely non-overlapping, and that past behavior in each modality is the most accurate predictor of future behavior in that modality. Results also show that browsing data provides a stronger source of signal than search queries due to its greater volume, which explains previous work that has found implicit behavioral data to be a valuable source of information for user modeling and personalization.

REFERENCES

• 1: Nick Craswell , Martin Szummer, Random walks on the click graph, Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, July 23-27, 2007, Amsterdam, The Netherlands [doi>10.1145/1277741.1277784]
• 2: Gauch, S., Speretta, M., Chandramouli, A., and Micarelli, A. (2007). User profiles for personalized information access. In The Adaptive Web, 54--89, Springer.
• 3: Feng Qiu , Junghoo Cho, Automatic identification of user interest for personalized search, Proceedings of the 15th international conference on World Wide Web, May 23-26, 2006, Edinburgh, Scotland [doi>10.1145/1135777.1135883]
• 4: Salton, G. and Buckley, C. (1990). Improving Retrieval Performance by Relevance Feedback. J. of the American Society for Information Science, 41(4), 288--297.
• 5: Taylor, R.(1968). Question negotiation and information seeking in libraries. College and Research Libraries, 29,178--194.
• 6: Jaime Teevan , Susan T. Dumais , Eric Horvitz, Personalizing search via automated analysis of interests and activities, Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval, August 15-19, 2005, Salvador, Brazil [doi>10.1145/1076034.1076111]
• 7: Yi Zhang , Jonathan Koren, Efficient bayesian hierarchical user modeling for recommendation system, Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, July 23-27, 2007, Amsterdam, The Netherlands [doi>10.1145/1277741.1277752]

INDEX TERMS

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

General Terms:
Experimentation, Human Factors, Measurement

Keywords:
personalization, predictive user modeling, user profiles