Collaborative information filtering: A review and an educational application

Andrew Walker, Mimi M. Recker, Kimberly Lawless, David Wiley

Research output: Contribution to journalArticlepeer-review

56 Scopus citations


This paper reviews the literature surrounding an information filtering technique, collaborative information filtering, which supports the discovery of resources in a way that is sensitive to the context of users. Moreover, via statistical clustering techniques, the system supports automated, personalized filtering and recommendation of relevant resources and like-minded users for particular user communities. The paper also describes an educational implementation of this approach, called Altered Vista, and presents results from a 3-month trial use of the system, aimed at evaluating the educational effectiveness and usefulness of the approach.

Original languageEnglish (US)
Pages (from-to)3-28
Number of pages26
JournalInternational Journal of Artificial Intelligence in Education
Issue number1
StatePublished - 2004

All Science Journal Classification (ASJC) codes

  • Education
  • Computational Theory and Mathematics


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