Author : Alaidine Ben Ayed
Affiliation : Université du Québec à Montréal (UQAM)
Country : Canada
Category : Computer Science & Information Technology
Abstract :
In this paper, we present VSMbM; a new metric for automatically generated text summaries evaluation. VSMbM is based on vector space modelling. It gives insights on to which extent retention and fidelity are met in the generated summaries. Two variants of the proposed metric, namely PCA-VSMbM and ISOMAP VSMbM, are tested and compared to Recall-Oriented Understudy for Gisting Evaluation (ROUGE): a standard metric used to evaluate automatically generated summaries. Conducted experiments on the Timeline17 dataset show that VSMbM scores are highly correlated to the state-of-the-art Rouge scores.
Volume, Issue, Month, Year : 10, 05, May, 2020
Keyword : Automatic Text Summarization, Automatic summary evaluation, Vector space modelling.
For More Details : https://aircconline.com/csit/papers/vol10/csit100510.pdf
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