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An Approach for Concept-based Automatic Multi-Document Summarization using Machine Learning

G. Padmapriya, K. Duraiswamy Published in Artificial Intelligence

International Journal of Applied Information Systems
Year of Publication 2012
© 2010 by IJAIS Journal
http:/ijais12-450491
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  1. G Padmapriya and K Duraiswamy. Article: An Approach for Concept-based Automatic Multi-Document Summarization using Machine Learning. International Journal of Applied Information Systems 3(3):49-53, July 2012. BibTeX

    @article{key:article,
    	author = "G. Padmapriya and K. Duraiswamy",
    	title = "Article: An Approach for Concept-based Automatic Multi-Document Summarization using Machine Learning",
    	journal = "International Journal of Applied Information Systems",
    	year = 2012,
    	volume = 3,
    	number = 3,
    	pages = "49-53",
    	month = "July",
    	note = "Published by Foundation of Computer Science, New York, USA"
    }
    

Abstract

Text Summarization is compressing the source text into a shorter version preserving its information content and overall meaning. It is very complicated for human beings to manually summarize large documents of text. Text summarization plays an important role in the area of natural language processing and text mining. Many approaches use statistics and machine learning techniques to extract sentences from documents. This paper presents an new approach for concept-based automatic multi-document summarization using machine learning.

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Keywords

Multi-document Summarization, Machine Learning