Research Article Open Access

Text Summarization Using Morphological Filtering of Intuitionistic Fuzzy Hypergraph

Dhanya Prabhasadanam Mohanan1, Sreekumar Ananda Rao1, Jathavedan Madambi1 and Ramkumar Padinjarepizharath Balakrishna2
  • 1 CUSAT, India
  • 2 RSET, India


Text Summarization has been an area of interest for many years. It refers to creating a concise text of a document without any lose of information. Researchers in the area of natural language processing have developed many abstractive and extractive methods for creating summary. Abstractive summaries modifies the sentences and creates a modified concise form, while extractive summaries pick relevant sentences. The extractive method used in this study is a novel one which models the document as an Intuitionistic Fuzzy Hypergraph (IFHG). This IFHG is subjected to morphological filtering in order to create a concise summary. This is the premier work which applies morphological operations on IFHG that is modeled on a text. The method has generated summary which is almost similar to a human generated summary and showed more accuracy when compared with other machine generated summaries.

Journal of Computer Science
Volume 14 No. 6, 2018, 837-853


Submitted On: 11 April 2018 Published On: 25 June 2018

How to Cite: Mohanan, D. P., Rao, S. A., Madambi, J. & Balakrishna, R. P. (2018). Text Summarization Using Morphological Filtering of Intuitionistic Fuzzy Hypergraph. Journal of Computer Science, 14(6), 837-853.

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  • Dilation
  • Erosion
  • Filter
  • Hypergraph
  • Intuitionistic Fuzzy