| dc.contributor.author | Masum, Abu Kaisar Mohammad | |
| dc.contributor.author | Abujar, Sheikh | |
| dc.contributor.author | Tusher, Raja Tariqul Hasan | |
| dc.contributor.author | Faisal, Fahad | |
| dc.contributor.author | Hossain, Syed Akhter | |
| dc.date.accessioned | 2021-11-01T08:09:00Z | |
| dc.date.available | 2021-11-01T08:09:00Z | |
| dc.date.issued | 2019-12-30 | |
| dc.identifier.uri | http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/6310 | |
| dc.description.abstract | Text summarization is a massive research area in natural language processing. It reduces the larger text and provided the prime meaning of a text document. Find the meaning of the larger text needed of a proper text analysis which gives a better text summarizer. Abstractive text summarizer gives a summary which can present or not present in the text document. The machine produces a text summary after learning from the human given summary. Sentence similarity is a way to judge a better text summarizer. It is exploring the similarity between sentences or words. This paper we discuss several methods of sentence similarity and proposed a method for identifying a better Bengali abstractive text summarizer. We used human given summary and machine response summary sentences for similarity measurement where both sentences contain a Bengali short text. There are several approaches to English sentences similarity measurement, and we applied some of the approaches for similarity measure for our Bengali text which give a satisfying result. For our given methods we collect data from online and social media and create a summary of those texts. After creating a summary pre-processing this text and generate a summary from our abstractive text summarization model. All summary sentence similarity measurement cases using the method provided an effective value and optimal result. | en_US |
| dc.language.iso | en_US | en_US |
| dc.publisher | 10th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2019, IEEE | en_US |
| dc.subject | Current measurement | en_US |
| dc.subject | Natural language processing | en_US |
| dc.subject | Numerical models | en_US |
| dc.subject | Social networking | en_US |
| dc.subject | Clustering algorithms | en_US |
| dc.subject | Estimation | en_US |
| dc.title | Sentence Similarity Measurement for Bengali Abstractive Text Summarization | en_US |
| dc.type | Article | en_US |