On the recommending of citations for research papers

Sean M. McNee, Istvan Albert, Dan Cosley, Prateep Gopalkrishnan, Shyong K. Lam, Al Mamunur Rashid, Joseph A. Konstan, John Riedl

Research output: Contribution to conferencePaperpeer-review

330 Scopus citations


Collaborative filtering has proven to be valuable for recommending items in many different domains. In this paper, we explore the use of collaborative filtering to recommend research papers, using the citation web between papers to create the ratings matrix. Specifically, we tested the ability of collaborative filtering to recommend citations that would be suitable additional references for a target research paper. We investigated six algorithms for selecting citations, evaluating them through offline experiments against a database of over 186,000 research papers contained in ResearchIndex. We also performed an online experiment with over 120 users to gauge user opinion of the effectiveness of the algorithms and of the utility of such recommendations for common research tasks. We found large differences in the accuracy of the algorithms in the offline experiment, especially when balanced for coverage. In the online experiment, users felt they received quality recommendations, and were enthusiastic about the idea of receiving recommendations in this domain.

Original languageEnglish (US)
Number of pages10
StatePublished - 2002
EventThe eight Conference on Computer Supported Cooperative Work (CSCW 2002) - New Orleans, LA, United States
Duration: Nov 16 2002Nov 20 2002


OtherThe eight Conference on Computer Supported Cooperative Work (CSCW 2002)
Country/TerritoryUnited States
CityNew Orleans, LA


  • Citation Graphs
  • Collaborative Filtering
  • Digital Libraries
  • Recommender Systems
  • ResearchIndex
  • Social Networks


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