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 |