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Title:CITREC: An Evaluation Framework for Citation-Based Similarity Measures based on TREC Genomics and PubMed Central
Author(s):Meuschke, Norman; Gipp, Bela; Lipinsk, Mario
Subject(s):data analytics and evaluation
recommender systems
information seeking/retrieval
Abstract:Citation-based similarity measures such as Bibliographic Coupling and Co-Citation are an integral component of many information retrieval systems. However, comparisons of the strengths and weaknesses of measures are challenging due to the lack of suitable test collections. This paper presents CITREC, an open evaluation framework for citation-based and text-based similarity measures. CITREC prepares the data from the PubMed Central Open Access Subset and the TREC Genomics collection for a citation-based analysis and provides tools necessary for performing evaluations of similarity measures. To account for different evaluation purposes, CITREC implements 35 citation-based and text-based similarity measures, and features two gold standards. The first gold standard uses the Medical Subject Headings (MeSH) thesaurus and the second uses the expert relevance feedback that is part of the TREC Genomics collection to gauge similarity. CITREC additionally offers a system that allows creating user defined gold standards to adapt the evaluation framework to individual information needs and evaluation purposes.
Issue Date:2015-03-15
Publisher:iSchools
Series/Report:iConference 2015 Proceedings
Genre:Conference Paper/Presentation
Type:Text
Language:English
URI:http://hdl.handle.net/2142/73680
Peer Reviewed:yes
Rights Information:Copyright 2015 is held by the authors. Copyright permissions, when appropriate, must be obtained directly from the authors.
Date Available in IDEALS:2015-03-24


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