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DC Field | Value | Language |
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dc.contributor.author | Prakash B.S. | |
dc.contributor.author | Sanjeev K.V. | |
dc.contributor.author | Prakash R. | |
dc.contributor.author | Chandrasekaran K. | |
dc.contributor.author | Rathnamma M.V. | |
dc.contributor.author | Ramana V.V. | |
dc.date.accessioned | 2021-05-05T10:16:15Z | - |
dc.date.available | 2021-05-05T10:16:15Z | - |
dc.date.issued | 2020 | |
dc.identifier.citation | Advances in Intelligent Systems and Computing , Vol. 1090 , , p. 557 - 565 | en_US |
dc.identifier.uri | https://doi.org/10.1007/978-981-15-1480-7_47 | |
dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/15030 | - |
dc.description.abstract | Summarization refers to the process of reducing the textual components such as words and sentences but conveying most of the information in the input text. Research in summarization is very prominent in the current scenario where the textual data available is enormous and contains valuable information. People have been interested in summarization since time immemorial. The methods adopted in the past relied on manually reading the text and based on one’s understanding of the text, manually generating the summary. In the current world, due to the explosion of data from Internet and social media, the manual process is very tedious and time-consuming. As a result, there is a great need to automate the process of summarization. In this paper, we summarize most of the researches in the field of summarization which is unique and path-breaking. © Springer Nature Singapore Pte Ltd. 2020. | en_US |
dc.title | Review of techniques for automatic text summarization | en_US |
dc.type | Conference Paper | en_US |
Appears in Collections: | 2. Conference Papers |
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