A New Approach for Single Text Document Summarization

  • Chandra Shekhar Yadav
  • Aditi Sharan
  • Rakesh Kumar
  • Payal Biswas
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 380)


This paper proposes an extraction-based hybrid model for a single text document summarization. The hybrid model is depending on the linear combination of statistical measures like sentence position, TF-IDF, aggregate similarity, centroid, and sentiment analysis. Our idea to include sentiment analysis for salient sentence extraction is derived from the concept that emotion plays an important role in communication to effectively convey any message; hence, it can play vital role in text document summarization. As we know for any sentence, emotions (calling sentiments) may be negative, positive, or neutral. Sentence which has strong sentiment are more important for us which may be either negative or positive.


Single document summarization Sentiment analysis Hybrid model 



Thanks to UGC for funding and special thanks to Iskandar Keskes (Miracl loboratory, ANLP-Research Group, Sfax-Tunisia), Ashish Kumar (SC & SS, LAB-01, JNU).


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Copyright information

© Springer India 2016

Authors and Affiliations

  • Chandra Shekhar Yadav
    • 1
  • Aditi Sharan
    • 1
  • Rakesh Kumar
    • 1
  • Payal Biswas
    • 1
  1. 1.SC & SS, Jawarlal Nehru UniversityNew DelhiIndia

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