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Sentence Similarity Using Syntactic and Semantic Features for Multi-document Summarization

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International Conference on Innovative Computing and Communications

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 56))

Abstract

Multi-Document Summarization (MDS) is a process obtaining precise and concise information from a specific set of documents which are on the same topic. The generated summary makes the user to understand the content in a set of documents. The existing approaches suffer with the lack of establishment of semantic and syntactic relationship among the words within a sentence. In this paper, a novel unsupervised MDS framework is proposed by ranking sentences using semantic and syntactic information embedded in the sentences. Empirical evaluations are carried using lexical, syntactic, and semantic features on DUC2002 dataset. The experimental results on DUC2002 prove that the proposed model is comparable with existing systems using various performance measures.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Dravidian University, Kuppam, India

    M. Anjaneyulu & K. Prem Chander

  2. CSE Department, Vaagdevi Engineering College, Warangal, India

    S. S. V. N. Sarma

  3. CSE Department, Matrusri Engineering College, Hyderabad, India

    P. Vijaya Pal Reddy

  4. Computer Science Department, S.R.R. Govterment Arts & Science College, Karimnagar, India

    S. Nagaprasad

Authors
  1. M. Anjaneyulu
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  2. S. S. V. N. Sarma
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  3. P. Vijaya Pal Reddy
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  4. K. Prem Chander
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  5. S. Nagaprasad
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Corresponding author

Correspondence to M. Anjaneyulu .

Editor information

Editors and Affiliations

  1. Department of Computer Application, RCC Institute of Information Technology, Kolkata, West Bengal, India

    Siddhartha Bhattacharyya

  2. Faculty of Computers and Information, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  3. Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology, New Delhi, Delhi, India

    Deepak Gupta

  4. Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology, New Delhi, Delhi, India

    Ashish Khanna

  5. Department of Information Technology, RCC Institute of Information Technology, Kolkata, West Bengal, India

    Indrajit Pan

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Anjaneyulu, M., Sarma, S.S.V.N., Vijaya Pal Reddy, P., Prem Chander, K., Nagaprasad, S. (2019). Sentence Similarity Using Syntactic and Semantic Features for Multi-document Summarization. In: Bhattacharyya, S., Hassanien, A., Gupta, D., Khanna, A., Pan, I. (eds) International Conference on Innovative Computing and Communications. Lecture Notes in Networks and Systems, vol 56. Springer, Singapore. https://doi.org/10.1007/978-981-13-2354-6_49

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