Paper Title

Machine Learning Techniques for Document Summarization: A Survey

Authors

  • Feny Mehta

Keywords

Automatic Document summarization, hierarchical clustering, k-means clustering, sentence scoring, sentence extraction.

Abstract

Currently huge amount of data is available on the internet which is increasing exponentially day by day. It becomes time consuming and tedious job to search a specific topic from the heap of information available. Document summarization is the key solution to the above stated problem. It refers to reducing the size of the document still preserving the main information of it. Abstractive and Extractive are the two main automatic document summarization techniques. The aim of this paper is to present a survey on various extractive document summarization techniques.

Article Type

Published

How To Cite

Feny Mehta. "Machine Learning Techniques for Document Summarization: A Survey".INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH ISSN:2321-9939, Vol.4, Issue 2, pp.659-664, URL :https://rjwave.org/ijedr/papers/IJEDR1602115.pdf

Issue

Volume 4 Issue 2 

Pages. 659-664

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