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Scientific document summarization in multi-objective clustering framework

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Abstract

The exponential growth in the number of scientific articles has made it difficult for the researchers to keep themselves updated with the new developments. Scientific document summarization solves this problem by providing a summary of essential contributions. In this paper, we have presented a novel method of scientific document summarization using a multi-objective differential evolution technique. Here, firstly distinct important sentences are extracted by using citation contextualization. These sentences are further clustered using the concept of multi-objective clustering. Two objective functions, PBM index, and XB index, measuring the compactness and separation of sentence clusters, are simultaneously optimized utilizing the search capability of multi-objective differential evolution. We have conducted our experiments on CL-SciSumm 2016, CL-SciSumm 2017, CL-SciSumm 2018, and CL-SciSumm 2019 datasets. Obtained results of CL-SciSumm 2016 and CL-SciSumm 2017 are compared with the state-of-the-art methods. Evaluation results demonstrate that our method outperforms others in terms of ROUGE-2, ROUGE-3, and ROUGE-SU4 scores.

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Notes

  1. https://tac.nist.gov/2014/BiomedSumm/

  2. https://github.com/WING-NUS/scisumm-corpus/

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Acknowledgements

This publication is an outcome of the R&D work undertaken in the project under the Visvesvaraya Ph.D. Scheme of Ministry of Electronics & Information Technology, Government of India, being implemented by Digital India Corporation (Formerly Media Lab Asia),

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Technology Patna, Patna, Bihar, India

    Santosh Kumar Mishra & Sriparna Saha

  2. Technology Studies, Endicott College of International Studies, Woosong University, Daejeon, South Korea

    Naveen Saini

  3. Department of Computer Science and Engineering, Indian Institute of Technology Bombay, Mumbai, Maharashtra, India

    Pushpak Bhattacharyya

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  1. Santosh Kumar Mishra
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Mishra, S.K., Saini, N., Saha, S. et al. Scientific document summarization in multi-objective clustering framework. Appl Intell 52, 1520–1543 (2022). https://doi.org/10.1007/s10489-021-02376-5

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