| dc.contributor.author | Hira Tauseef, 01-243182-009 | |
| dc.date.accessioned | 2022-01-17T10:26:57Z | |
| dc.date.available | 2022-01-17T10:26:57Z | |
| dc.date.issued | 2021 | |
| dc.identifier.uri | http://hdl.handle.net/123456789/11648 | |
| dc.description | Supervised by Dr. Muhammad Asfand-e-Yar | en_US |
| dc.description.abstract | The abundance of online information may be the best and worst thing that has happened in the past decade. The overwhelming amount of information may be a lot for the consumers to absorb and retain. Various methods have been developed over the years to tackle the issue of over-burdening consumers and the research has led to the topic of text summarization. Text summarization is the method of producing a concise version of text by retaining the most relevant information. Most of the existing studies revolve around unsupervised methods and smaller documents. The method proposed in paper provides a parallel view of supervised and unsupervised methods and gives an insight on both approaches through experimentation and analysis. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Computer Sciences BUIC | en_US |
| dc.relation.ispartofseries | MS (CS);T-9672 | |
| dc.subject | Efficient Scheme | en_US |
| dc.subject | Extractive Summarization | en_US |
| dc.title | An Efficient Scheme for Extractive Summarization of Text | en_US |
| dc.type | MS Thesis | en_US |