@inproceedings{kajiwara-fujita-2017-semantic,
title = "Semantic Features Based on Word Alignments for Estimating Quality of Text Simplification",
author = "Kajiwara, Tomoyuki and
Fujita, Atsushi",
editor = "Kondrak, Greg and
Watanabe, Taro",
booktitle = "Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)",
month = nov,
year = "2017",
address = "Taipei, Taiwan",
publisher = "Asian Federation of Natural Language Processing",
url = "https://aclanthology.org/I17-2019",
pages = "109--115",
abstract = "This paper examines the usefulness of semantic features based on word alignments for estimating the quality of text simplification. Specifically, we introduce seven types of alignment-based features computed on the basis of word embeddings and paraphrase lexicons. Through an empirical experiment using the QATS dataset, we confirm that we can achieve the state-of-the-art performance only with these features.",
}
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<abstract>This paper examines the usefulness of semantic features based on word alignments for estimating the quality of text simplification. Specifically, we introduce seven types of alignment-based features computed on the basis of word embeddings and paraphrase lexicons. Through an empirical experiment using the QATS dataset, we confirm that we can achieve the state-of-the-art performance only with these features.</abstract>
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%0 Conference Proceedings
%T Semantic Features Based on Word Alignments for Estimating Quality of Text Simplification
%A Kajiwara, Tomoyuki
%A Fujita, Atsushi
%Y Kondrak, Greg
%Y Watanabe, Taro
%S Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)
%D 2017
%8 November
%I Asian Federation of Natural Language Processing
%C Taipei, Taiwan
%F kajiwara-fujita-2017-semantic
%X This paper examines the usefulness of semantic features based on word alignments for estimating the quality of text simplification. Specifically, we introduce seven types of alignment-based features computed on the basis of word embeddings and paraphrase lexicons. Through an empirical experiment using the QATS dataset, we confirm that we can achieve the state-of-the-art performance only with these features.
%U https://aclanthology.org/I17-2019
%P 109-115
Markdown (Informal)
[Semantic Features Based on Word Alignments for Estimating Quality of Text Simplification](https://aclanthology.org/I17-2019) (Kajiwara & Fujita, IJCNLP 2017)
ACL