Scopus Indexed Paper

Paper Details


Title
Sentence Similarity Measurement for Bengali Abstractive Text Summarization
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.
Keywords
Text Summarization, Bengali Abstractive Summarization, Sentence Similarity, Text Pre-processing, Natural Language Processing
Authors
Abu Kaisar Mohammad Masum, Sheikh Abujar, Raja Tariqul Hasan Tusher, Fahad Faisal, Syed Akhter Hossain
Phone
Journal or Conference Name
2019 10th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2019
Publish Year
2019
Indexing
Scopus