Technology-Assisted Review (TAR) systems are essential to minimize the effort of the user during the search and retrieval of relevant documents for a specific information need. In this paper, we present a failure analysis based on terminological and linguistic aspects of a TAR system for systematic medical reviews. In particular, we analyze the results of the worst performing topics in terms of recall using the dataset of the CLEF 2017 eHealth task on TAR in Empirical Medicine.

A linguistic failure analysis of classification of medical publications: A study on stemming vs lemmatization

Di Nunzio, Giorgio Maria
;
Vezzani, Federica
2018

Abstract

Technology-Assisted Review (TAR) systems are essential to minimize the effort of the user during the search and retrieval of relevant documents for a specific information need. In this paper, we present a failure analysis based on terminological and linguistic aspects of a TAR system for systematic medical reviews. In particular, we analyze the results of the worst performing topics in terms of recall using the dataset of the CLEF 2017 eHealth task on TAR in Empirical Medicine.
2018
Proceedings of the Fifth Italian Conference on Computational Linguistics CLiC-it 2018
9788831978682
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3302620
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