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Paper Details
Paper Title
Machine Learning Techniques for Document Summarization: A Survey
Authors
Feny Mehta
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.
Keywords- Automatic Document summarization, hierarchical clustering, k-means clustering, sentence scoring, sentence extraction.
Publication Details
Unique Identification Number - IJEDR1602115Page Number(s) - 659-664Pubished in - Volume 4 | Issue 2 | May 2016DOI (Digital Object Identifier) - Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
Feny Mehta, "Machine Learning Techniques for Document Summarization: A Survey", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.4, Issue 2, pp.659-664, May 2016, Available at :http://www.ijedr.org/papers/IJEDR1602115.pdf
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