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A Metric for Sentence Ordering Assessment Based on Topic-Comment Structure

Abstract : Sentence ordering (SO) is a key component of verbal ability. It is also crucial for automatic text generation. While numerous researchers developed various methods to automatically evaluate the informativeness of the produced contents, the evaluation of readability is usually performed manually. In contrast to that, we present a self-sufficient metric for SO assessment based on text topic-comment structure. We show that this metric has high accuracy.
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https://hal.archives-ouvertes.fr/hal-01873782
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Submitted on : Thursday, September 13, 2018 - 3:46:52 PM
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  • HAL Id : hal-01873782, version 1
  • OATAO : 19035

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Liana Ermakova, Josiane Mothe, Anton Firsov. A Metric for Sentence Ordering Assessment Based on Topic-Comment Structure. 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2017), Aug 2017, Tokyo, Japan. pp. 1061-1064. ⟨hal-01873782⟩

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