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Content-based recommendation for Academic Expert finding

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Published:26 June 2018Publication History

ABSTRACT

Nowadays it is more and more frequent that Web users search for professionals in order to find people who can help solve any problem in a given field. This is call expert finding. A particular case is when users are interested in scientific researchers. The associated problem is to get, given a query that expresses a topic of interest for a user, a set of researchers who are expert on it. One of the difficulties to tackle the problem is to indentify the topics in which a professional is expert. In this paper, we face this problem from a content-based recommendatation perspective and we present a method where, starting from the articles published by each researcher, and a query, the expert researchers are obtained. We also present a new document collection, called PMSC-UGR, specifically designed for the evaluation in the field of expert finding and document filtering

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              cover image ACM Other conferences
              CERI '18: Proceedings of the 5th Spanish Conference on Information Retrieval
              June 2018
              91 pages
              ISBN:9781450365437
              DOI:10.1145/3230599

              Copyright © 2018 ACM

              © 2018 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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              Publication History

              • Published: 26 June 2018

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              CERI '18 Paper Acceptance Rate18of24submissions,75%Overall Acceptance Rate36of51submissions,71%
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