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http://hdl.handle.net/2080/2656
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DC Field | Value | Language |
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dc.contributor.author | Naidu, Reddy | - |
dc.contributor.author | Bharti, Santosh Kumar | - |
dc.contributor.author | Sathya Babu, Korra | - |
dc.contributor.author | Mohapatra, Ramesh Kumar | - |
dc.date.accessioned | 2017-03-06T13:13:14Z | - |
dc.date.available | 2017-03-06T13:13:14Z | - |
dc.date.issued | 2017-03 | - |
dc.identifier.citation | 1st International Conference on Smart Computing and Informatics(SCI), ANITS, Visakhapatnam, India, 3-4 Mar 2017 | en_US |
dc.identifier.uri | http://hdl.handle.net/2080/2656 | - |
dc.description | Copyright belongs to the proceeding publisher | en_US |
dc.description.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 | en_US |
dc.subject | Automatic Keyword Extraction | en_US |
dc.subject | e-Newspapers | en_US |
dc.subject | NLP | en_US |
dc.subject | Summerization | en_US |
dc.subject | Telugu | en_US |
dc.title | Text Summarization with Automatic Keyword Extraction in Telugu e-Newspapers | en_US |
dc.type | Article | en_US |
Appears in Collections: | Conference Papers |
Files in This Item:
File | Description | Size | Format | |
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2017_ICSSI_KSBabu_Text.pdf | 630.16 kB | Adobe PDF | View/Open |
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