Alharbi, A. and Stevenson, M. orcid.org/0000-0002-9483-6006 (2017) Ranking abstracts to identify relevant evidence for systematic reviews: The University of Sheffield's approach to CLEF eHealth 2017 Task 2: Working notes for CLEF 2017. In: Cappellato, L., Ferro, N., Goeuriot, L. and Mandl, T., (eds.) CEUR Workshop Proceedings. Conference and Labs of the Evaluation Forum (CLEF 2017), 11-14 Sep 2017, Dublin, Ireland. CEUR
Abstract
This paper describes Sheffield University's submission to CLEF 2017 eHealth Task 2: Technologically Assisted Reviews in Empirical Medicine. This task focusses on the identification of relevant evidence for systematic reviews in the medical domain. Participants are provided with systematic review topics (including title, Boolean query and set of PubMed abstracts returned) and asked to identify the abstracts that provide evidence relevant to the review topic. Sheffield University participated in the simple evaluation. Our approach was to rank the set of PubMed abstracts returned by the query by making use of information in the topic including title and Boolean query. Ranking was based on a simple TF.IDF weighted cosine similarity measure. This paper reports results obtained from six runs: four submitted to the official evaluation, an additional run and a baseline approach.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2017 The Author(s). Reproduced in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 15 Mar 2018 16:11 |
Last Modified: | 15 Mar 2018 16:11 |
Published Version: | http://ceur-ws.org/Vol-1866/paper_97.pdf |
Status: | Published |
Publisher: | CEUR |
Refereed: | Yes |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:128574 |