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Soft Computing in Data Analytics pp 483–492Cite as

Single-Sentence Compression Using SVM

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 758))

Abstract

Presenting a sentence in less number of words compared to its original one without changing the meaning is known as sentence compression. Most recent works on sentence compression models define the problem as an integer linear programming problem and solve it using an external ILP-solver which suffers from slow running time. In this paper, we have presented a machine learning approach to single-sentence compression. The sentence compression task is modeled as a two-class classification problem and used support vector machine to solve the problem. Different learning models are created using different types of kernel functions. Finally, it has been observed that RBF kernel gives good result compared to other kernel functions for this compression task of single sentence.

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Notes

  1. 1.

    https://www.ling.upenn.edu/courses/Fall_2003/ling001/penn_treebank_pos.html.

  2. 2.

    http://storage.googleapis.com/sentencecomp/compression-data.json.

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Author information

Authors and Affiliations

  1. Department of CSE, IIIT-Bhubaneswar, Bhubaneswar, 751003, Odisha, India

    Deepak Sahoo & Rakesh Chandra Balabantaray

Authors
  1. Deepak Sahoo
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  2. Rakesh Chandra Balabantaray
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Corresponding author

Correspondence to Deepak Sahoo .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Sri Sivani College of Engineering, Srikakulam, Andhra Pradesh, India

    Janmenjoy Nayak

  2. Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research Excellence, Washington, USA

    Ajith Abraham

  3. Department of Mechanical Engineering, Sri Sivani College of Engineering, Srikakulam, Andhra Pradesh, India

    B. Murali Krishna

  4. Department of Electrical and Electronics Engineering, Sri Sivani College of Engineering, Srikakulam, Andhra Pradesh, India

    G. T. Chandra Sekhar

  5. Department of Computer Science and Technology, Indian Institute of Engineering Science and Technology (IIEST), Shibpur, Howrah, West Bengal, India

    Asit Kumar Das

Appendix 1

Appendix 1

Table 5 Sentences that are grammatically correct and informative (category A)
Full size table
Table 6 Sentences that are grammatically correct and Informative but few extra words (category B) given in brackets
Full size table
Table 7 Sentences that are grammatically incorrect (C)
Full size table

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Cite this paper

Sahoo, D., Balabantaray, R.C. (2019). Single-Sentence Compression Using SVM. In: Nayak, J., Abraham, A., Krishna, B., Chandra Sekhar, G., Das, A. (eds) Soft Computing in Data Analytics . Advances in Intelligent Systems and Computing, vol 758. Springer, Singapore. https://doi.org/10.1007/978-981-13-0514-6_48

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