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ZENODO
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ZENODO
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Document-to-document relevant assessment for TREC Genomics Track 2005

Authors: Olga Giraldo; Dhwani Solanki; Fernanda Cadena; Andrea Robayo-Gama; Dietrich Rebholz-Schuhmann; Leyla Jael Castro;

Document-to-document relevant assessment for TREC Genomics Track 2005

Abstract

Here we present a table with document-to-document relevance assessment judgements on a subset of the TREC Genomics Track 2005 which corresponds to document-to-topic relevance assessments. This data was produced by four annotators to make it possible to analyze inter-annotator agreements as part of our future work. The data was produced with and in-house annotation tool tailored to the initial TREC data and the task at hand. The "raw data document evaluation" contains six columns, first row consecutive id, second original TREC topic, third PubMed Id used as reference document, fourth PMID used to evaluate the relevance wrt the reference document, fifth the relevance score (2 definitely relevant, 1 partially relevant, 0 non-relevant), and sixth annotator id. Acknowledgements This work is part of the STELLA project funded by DFG (project no. 407518790). This work was supported by the BMBF-funded de.NBI Cloud within the German Network for Bioinformatics Infrastructure (de.NBI) (031A532B, 031A533A, 031A533B, 031A534A, 031A535A, 031A537A, 031A537B, 031A537C, 031A537D, 031A538A).

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Keywords

Relevance assessment, document similarity, literature manual curation

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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