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Scholarly paper recommendation via user's recent research interests

Online:21 June 2010Publication History

ABSTRACT

We examine the effect of modeling a researcher's past works in recommending scholarly papers to the researcher. Our hypothesis is that an author's published works constitute a clean signal of the latent interests of a researcher. A key part of our model is to enhance the profile derived directly from past works with information coming from the past works' referenced papers as well as papers that cite the work. In our experiments, we differentiate between junior researchers that have only published one paper and senior researchers that have multiple publications. We show that filtering these sources of information is advantageous -- when we additionally prune noisy citations, referenced papers and publication history, we achieve statistically significant higher levels of recommendation accuracy.

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              ACM Conferences cover image
              JCDL '10: Proceedings of the 10th annual joint conference on Digital libraries
              June 2010
              424 pages
              ISBN:9781450300858
              DOI:10.1145/1816123

              Copyright © 2010 ACM

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              Association for Computing Machinery

              New York, NY, United States

              Publication History

              • Online: 21 June 2010

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              Overall Acceptance Rate 334 of 1,195 submissions, 28%

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