TITLE:
Construction of an Automatic Bengali Text Summarizer Using Machine Learning Approaches
AUTHORS:
Busrat Jahan, Mahfuja Khatun, Zinat Ara Zabu, Afranul Hoque, Sayed Uddin Rayhan
KEYWORDS:
Natural Language Processing, Formatting, Bangla Text Summarizer, Bengali Language Processing, Word Tagging, Pronoun Replacement, Sentence Ranking
JOURNAL NAME:
Journal of Data Analysis and Information Processing,
Vol.10 No.1,
February
9,
2022
ABSTRACT: In our study, we chose python as the programming platform for finding an Automatic Bengali Document Summarizer. English has sufficient tools to process and receive summarized records. However, there is no
specifically applicable to Bengali since Bengali has a lot of ambiguity, it
differs from English in terms of grammar. Afterward,
this language holds an important place because this language is spoken by 26 core
people all over the world. As a result, it has taken a new method to summarize Bengali documents.
The proposed system has been designed by
using the following stages: pre-processing the sample doc/input doc,
word tagging, pronoun replacement, sentence ranking, as well as summary. Pronoun replacement has been used to
reduce the incidence of swinging
pronouns in the performance review. We ranked sentences based on
sentence frequency, numerical figures, and pronoun replacement. Checking the
similarity between two sentences in order to exclude one since it has less duplication. Hereby, we’ve taken 3000 data as input from newspaper and book documents
and learned the words to be appropriate with syntax. In addition, to evaluate the performance of the
designed summarizer, the design system
looked at the different documents. According to the assessment method, the recall, precision, and F-score were 0.70, 0.82 and 0.74, respectively, representing 70%, 82% and 74% recall,
precision, and F-score. It has been found that the proper pronoun replacement was 72%.