Ermakova, Liana and Mothe, Josiane
and Firsov, Anton
A Metric for Sentence Ordering Assessment Based on Topic-Comment Structure.
(2017)
In: 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2017), 7 August 2017 - 11 August 2017 (Tokyo, Japan).
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(Document in English)
PDF (Author's version) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader 146kB |
Official URL: http://doi.org/10.1145/3077136.3080720
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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