Studying the Effect of Syntactic Simplification on Text Summarization

计算机科学 自动汇总 自然语言处理 人工智能 文本简化 解析 情报检索 语言学 判决 哲学
作者
Niladri Chatterjee,Raksha Agarwal
出处
期刊:Iete Technical Review 卷期号:40 (2): 155-166 被引量:8
标识
DOI:10.1080/02564602.2022.2055670
摘要

The need for automatic text summarization (ATS) is increased manifold in recent times due to the overwhelming growth of textual data available in electronic form. However, existing ATS systems suffer from two major shortcomings. Summarizers of extractive type, that is, the ones which select important sentences of the documents in their original form as the output, tend to copy some irrelevant or unimportant parts of the input text in the output summary. On the other hand, abstractive summarizers, that is, the ones that produce a gist of the limited size of the original document, often fail to include important contents in the generated summary. Simplification of the input texts before submitting them to the ATS system(s) may obliterate the above difficulties. The present work examines the effectiveness of simplification of input for five different known ATS systems. In this work, DEPSYM++ simplifier has been used for the above purpose, which carries out four different kinds of simplification on sentences of the input text corresponding to the presence of appositive clause, relative clause, conjoint clause, and passive voice. The results obtained are found to be very encouraging when experiments were carried out on three different gold data sets and under different evaluation metrics commonly used for performance evaluation for summarizers.
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