| dc.contributor.advisor | ||
| dc.contributor.author | Siriwardena, K.D. Isuru Amantha | |
| dc.date.accessioned | 2019-03-04T10:27:22Z | |
| dc.date.available | 2019-03-04T10:27:22Z | |
| dc.date.issued | 2018 | |
| dc.identifier.citation | Siriwardena, K. D. I. A. (2018) Sārānshā - Generating Mind Maps in Sinhala from Extractive Text Summarization. BSc. Dissertation. Informatics Institute of Technology | en_US |
| dc.identifier.other | 2014217 | |
| dc.identifier.uri | http://dlib.iit.ac.lk/xmlui/handle/123456789/158 | |
| dc.description.abstract | When it comes to the exam time, most of the students cannot remember the things they have learned or studied. Studying or remembering things is actually a really complex procedure and researches have shown that there is a “right” and a “wrong” way to do it. Creating summaries, mind maps, flash cards and writing questions to flashback the memory are some of the ways that are considered right to remember things. In the modern world due to lack of the time, generating an accurate and intelligent summary for a long document or text pieces has become a popular research as well as an industry problem. The field of automatic text summarization has evolved since 1950’s. In 2004 with the adaptation of Unicode technology into the internet, Sinhala language also faced the above problem. This research has proposed a solution for summarizing the text in Sinhala language by identifying the most important and relevant sentences based on linguistic and statistical features of the text, using unsupervised extractive summarization approach. In order to generate a better summary, keyword and sentences extraction is manipulated by using a graph based TextRank algorithm. | en_US |
| dc.subject | Graph theory | en_US |
| dc.subject | Natural Language Processing | en_US |
| dc.title | Sārānshā - Generating Mind Maps in Sinhala from Extractive Text Summarization | en_US |
| dc.type | Thesis | en_US |