Measuring user preference changes in digital libraries

Yang Sun, Huajing Li, Isaac G. Councill, Wang Chien Lee, C. Lee Giles

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Much research has been conducted using web access logs to study implicit user feedback and infer user preferences from clickstreams. However, little research measures the changes of user preferences of ranking documents over time. We present a study that measures the changes of user preferences based on an analysis of access logs of a large scale digital library over one year. A metric based on the accuracy of predicting future user actions is proposed. The results show that although user preferences change over time, the majority of user actions should be predictable from previous browsing behavior in the digital library.

Original languageEnglish (US)
Title of host publicationProceedings of the 17th ACM Conference on Information and Knowledge Management, CIKM'08
Pages1497-1498
Number of pages2
DOIs
StatePublished - Dec 1 2008
Event17th ACM Conference on Information and Knowledge Management, CIKM'08 - Napa Valley, CA, United States
Duration: Oct 26 2008Oct 30 2008

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Other

Other17th ACM Conference on Information and Knowledge Management, CIKM'08
CountryUnited States
CityNapa Valley, CA
Period10/26/0810/30/08

All Science Journal Classification (ASJC) codes

  • Decision Sciences(all)
  • Business, Management and Accounting(all)

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  • Cite this

    Sun, Y., Li, H., Councill, I. G., Lee, W. C., & Giles, C. L. (2008). Measuring user preference changes in digital libraries. In Proceedings of the 17th ACM Conference on Information and Knowledge Management, CIKM'08 (pp. 1497-1498). (International Conference on Information and Knowledge Management, Proceedings). https://doi.org/10.1145/1458082.1458353