For many years, text summarization has piqued people's interest. It refers to condensing a document's text without losing any information. Many abstractive and extractive strategies for constructing summaries have been developed by researchers in the field of natural language processing. Extractive summaries select relevant sentences, but abstractive summaries modify the sentences and create a modified compact form. This work employs a unique extraction method that models the document as an Intuitionistic Fuzzy Hypergraph (IFHG). The work's major goals are to transform a document into an IFHG, perform morphological operations on it, and build a summary filter. This is the first study to use morphological procedures on an IFHG modelled on a text. When compared to previous machine-generated summaries, the approach produced a summary that is practically identical to a human-generated summary and exhibited higher accuracy. An attempt is also made to apply the skelton procedure to a text hypergraph.
Author (S) Details
Dhanya Prabhasadanam Mohanan
Department of Computer Science, RSET, Kochi, India.
Sreekumar Ananda Rao
Department of Computer Applications, CUSAT, Kochi, India.
Jathavedan Madambi
Department of Computer Applications, CUSAT, Kochi, India.
Ramkumar Padinjarepizharath Balakrishna
Department of Basic Sciences and Humanities, RSET, Kochi, India.
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