Please use this identifier to cite or link to this item: https://doi.org/10.1145/1816123.1816129
Title: Scholarly paper recommendation via user's recent research interests
Authors: Sugiyama, K. 
Kan, M.-Y. 
Keywords: Digital library
Information retrieval
Recommendation
User modeling
Issue Date: 2010
Source: Sugiyama, K.,Kan, M.-Y. (2010). Scholarly paper recommendation via user's recent research interests. Proceedings of the ACM International Conference on Digital Libraries : 29-38. ScholarBank@NUS Repository. https://doi.org/10.1145/1816123.1816129
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. © 2010 ACM.
Source Title: Proceedings of the ACM International Conference on Digital Libraries
URI: http://scholarbank.nus.edu.sg/handle/10635/40291
ISBN: 9781450300858
DOI: 10.1145/1816123.1816129
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