[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.9708/jksci.2019.24.07.031

Citation-based Article Summarization using a Combination of Lexical Text Similarities: Evaluation with Computational Linguistics Literature Summarization Datasets

Kang, In-Su (Dept. of Computer Science, Kyungsung University)

Publication Information

Journal of the Korea Society of Computer and Information / v.24, no.7, 2019 , pp. 31-37 More about this Journal

Abstract

Citation-based article summarization is to create a shortened text for an academic article, reflecting the content of citing sentences which contain other's thoughts about the target article to be summarized. To deal with the problem, this study introduces an extractive summarization method based on calculating a linear combination of various sentence salience scores, which represent the degrees to which a candidate sentence reflects the content of author's abstract text, reader's citing text, and the target article to be summarized. In the current study, salience scores are obtained by computing surface-level textual similarities. Experiments using CL-SciSumm datasets show that the proposed method parallels or outperforms the previous approaches in ROUGE evaluations against SciSumm-2017 human summaries and SciSumm-2016/2017 community summaries.

Keywords

Citation; Summarization; Text Similarity;

Citations & Related Records

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