Deokate Auto Text Summarization
| dc.contributor.author | Deokate, Sayali | |
| dc.date.accessioned | 2021-07-16T13:05:03Z | |
| dc.date.available | 2021-07-16T13:05:03Z | |
| dc.date.created | 2020 | |
| dc.description | 2020 Celebration of Student Research and Creativity presentation | en_US |
| dc.description.abstract | Summarization is defined as taking a lot of information and creating a condensed and objective account of the key ideas and features of a text. It saves our time as we do not have to go through each and every detail in a document or text. Hence, a summary must be short, representative and readable. Automatic Text Summarization focuses on the bigger picture rather than expanding on smaller details. In this work, we will discuss different works in automatic summarization that have already been done. We will also compare the results of different summarization techniques based on parameters like code complexity, the accuracy of the summaries obtained. | en_US |
| dc.description.uri | https://youtu.be/mxOP1sJAD9k | en_US |
| dc.identifier.uri | http://hdl.handle.net/11216/3749 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Northern Kentucky University | en_US |
| dc.relation.ispartofseries | Celebration of Student Research and Creativity;2020 | |
| dc.subject | Information storage and retrieval systems Abstracts | en_US |
| dc.title | Deokate Auto Text Summarization | en_US |
| dc.type | Presentation | en_US |