Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
The link prediction problem for social networks
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Unsupervised prediction of citation influences
Proceedings of the 24th international conference on Machine learning
Comparative experiments on learning information extractors for proteins and their interactions
Artificial Intelligence in Medicine
Co-authorship networks in the digital library research community
Information Processing and Management: an International Journal - Special issue: Infometrics
The web as a graph: measurements, models, and methods
COCOON'99 Proceedings of the 5th annual international conference on Computing and combinatorics
Research paper recommender system evaluation: a quantitative literature survey
Proceedings of the International Workshop on Reproducibility and Replication in Recommender Systems Evaluation
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In this paper we explore the usefulness of various types of publication-related metadata, such as citation networks and curated databases, for the task of identifying genes in academic biomedical publications. Specifically, we examine whether knowing something about which genes an author has previously written about, combined with information about previous coauthors and citations, can help us predict which new genes the author is likely to write about in the future. Framed in this way, the problem becomes one of predicting links between authors and genes in the publication network. We show that this solely social-network based link prediction technique outperforms various baselines, including those relying only on non-social biological information.