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Text Mining Scientific Data to Extract Relevant Documents and Auto -Summarization


Author(s):

Sarika Davare , Fr. CRCE Bandra, Mumbai ; Devika Sindhawani, Fr.CRCE Bandra; Prince Castelino, Fr. CRCE Bandra; Anu George, Fr. CRCE Bandra

Keywords:

RAKE, MEAD, NLP Techniques

Abstract:

A search using text mining will identify facts, relationships and assertions that would otherwise remain buried in a mass of big data. As the problem of information overload has grown, and as the quantity of data has increased, so has interest in automatic summarization. Automatic summarization is the process of reducing a text document with a computer program in order to create a summary that retains the most important points of the original document. Multi-document summarization aims at extraction of information from multiple texts written about the same topic. The resulting summary report allows individual users, such as professional information consumers, to quickly familiarize themselves with the information contained in a large cluster of documents. The proposed system aims at combining text mining techniques with summarization to help segregate required information from the stack of available information and thus save on user’s time and provide better analytical results.


Other Details:

Manuscript Id :IJSTEV4I2041
Published in :Volume : 4, Issue : 2
Publication Date: 01/09/2017
Page(s): 109-114
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