A Survey on Query based Automatic Text Summarization

Authors

  • Payolina Nanda  Scholar, Department of computer science and information technology, ITER, SOA University, Bhubaneswar, Odisha, India
  • Dr. Ajit Kumar Nayak  Head of the department, Department of computer science and information technology, ITER, SOA University, Bhubaneswar, Odisha, India

Keywords:

Automatic text summarization, Query based extractive text summarization, Single and multi-document, graph based approach, machine learning approach, sentence scoring method

Abstract

Text summarization is an important problem in natural language processing (NLP). The process in which collection of crucial information takes place from an original document and representing its information in the form of a summary is known as Automatic Text Summarization . We know the history has been an evidence where it is a tasking job for a human being to synopsize a bulk document and a time consuming job to create a summary from the document by considering the key points and the essence of the document. There are two genres of text summarization and it has been categorized as extractive method and abstractive method. Here in our study we will be mainly focusing on extractive text summarization based on a query defined by the user. The maximum inquiring problem in text summarization is to produce a brief text which is elucidative depending on the query given by the user. The problem here for query based text summarization has been plenteously researched and many techniques have been designed for its elucidation. But we need a path landing solution which will provide informative summary without containing any redundancy and ambiguity and which will produce a fluent, well-organised summary for a given query. An inspection which has been carried out here for query-based summarization approach with their accession for single and multi-document summarization, primarily basing on knowledge forms and machine level learning routines. Other than this there are different methods for choosing the highly correlated sentence from the source document with respect to a given query.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2018-04-30

Issue

Volume 3, Issue 3, March-April-2018

Section

Research Articles

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How to Cite

[1]
Payolina Nanda, Dr. Ajit Kumar Nayak, " A Survey on Query based Automatic Text Summarization, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 3, pp.1332-1340, March-April-2018.