Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/2656
Title: Text Summarization with Automatic Keyword Extraction in Telugu e-Newspapers
Authors: Naidu, Reddy
Bharti, Santosh Kumar
Sathya Babu, Korra
Mohapatra, Ramesh Kumar
Keywords: Automatic Keyword Extraction
e-Newspapers
NLP
Summerization
Telugu
Issue Date: Mar-2017
Citation: 1st International Conference on Smart Computing and Informatics(SCI), ANITS, Visakhapatnam, India, 3-4 Mar 2017
Abstract: Summarization is the process of shortening a text document to make a summary that keeps the main points of the actual document. Extractive summarizers work on the given text to extract sentences that best express the message hidden in the text. Most extractive summarization techniques revolve around the concept of finding keywords and extracting sentences that have more keywords than the rest. Keyword extraction usually is done by extracting relevant words having a higher frequency than others, with stress on important ones’. Manual extraction or annotation of keywords is a tedious process brimming with errors involving lots of manual effort and time. In this work, we proposed an algorithm that automatically extracts keyword for text summarization in Telugu e-newspaper datasets. The proposed method compares with the experimental result of articles having the similar title in five different Telugu e-Newspapers to check the similarity and consistency in summarized results
Description: Copyright belongs to the proceeding publisher
URI: http://hdl.handle.net/2080/2656
Appears in Collections:Conference Papers

Files in This Item:
File Description SizeFormat 
2017_ICSSI_KSBabu_Text.pdf630.16 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.