Information Retrieval
Automatic language and information processing: rethinking evaluation
Natural Language Engineering
Evaluating the evaluation: a case study using the TREC 2002 question answering track
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Toward breast cancer survivability prediction models through improving training space
Expert Systems with Applications: An International Journal
Natural language processing: a prolog perspective
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Automatic classification of medical reports, the CIREA project
TELE-INFO'06 Proceedings of the 5th WSEAS international conference on Telecommunications and informatics
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F-measure is an indicator which has been commonly used for 25 years to evaluate classification algorithms in textmining, based on precision and recall. For classification and information retrieval, some prefer to use the break even point. Nevertheless, these measures have some inconvenient: they use a binary logic and don't allow to apply a user (judge) assessment. This paper proposes a new approach for evaluation. First, we distinguish classification and categorization from a semantic point of view. Then, we introduce a new measure: the K-measure, which is an overall of F-measure, and allows to apply user requirements. Finally, we propose a methodology for evaluation.