A New Metric of Validation for Automatic Text Summarization by Extraction

Ahmed Chaouki Lokbani
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Ahmed Chaouki Lokbani: Department of Computer Science, Dr. Tahar Moulay University of Saida, Saida, Algeria

International Journal of Strategic Information Technology and Applications (IJSITA), 2017, vol. 8, issue 3, 20-40

Abstract: In this article, the author proposes a new metric of evaluation for automatic summaries of texts. In this case, the adaptation of the F-measure that generates a hybrid method of evaluating an automatic summary at the same time as both extrinsic and intrinsic. The article starts by studying the feasibility of adaptation of the F-measure for the evaluation of automatic summarization. After that, the author defines how to calculate the F-measure for a candidate summary. Text is presented with a term vector which can be either a word or a phrase, with a binary-weighted or occurrence. Finally, to determine to the exactitude of evaluation of the F-measure for automatic summarization by extraction calculates correlation with the ROUGE Evaluation.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jsita0:v:8:y:2017:i:3:p:20-40

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