检索结果-南通市图书馆

Construction of an Automatic Bengali Text Summarizer Using Machine Learning Approaches

Journal of Data Analysis and Information Processing 2022年第1期10卷 43-57页

作者： busrat jahan Mahfuja Khatun Zinat Ara Zabu Afranul Hoque Sayed Uddin Rayhan Department of Computer Science & Engineering Feni University Feni Bangladesh Department of Computer Science & Engineering United International University Dhaka Bangladesh

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%.

关键词： Natural Language Processing Formatting Bangla Text Summarizer Bengali Language Processing Word Tagging Pronoun Replacement Sentence Ranking

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Next Words Prediction and Sentence Completion in Bangla Language Using GRU-Based RNN on N-Gram Language Model

引用

Journal of Data Analysis and Information Processing 2023年第4期11卷 388-399页

作者： Afranul Hoque busrat jahan Shaikat Chandra Paul Zinat Ara Zabu Rakhi Mondal Papeya Akter Department of Computer Science and Engineering Feni University Feni Bangladesh Department of Computer Science and Engineering National University Dhaka Bangladesh

We use a lot of devices in our daily life to communicate with others. In this modern world, people use email, Facebook, Twitter, and many other social network sites for exchanging information. People lose their valuable time misspelling and retyping, and some people are not happy to type large sentences because they face unnecessary words or grammatical issues. So, for this reason, word predictive systems help to exchange textual information more quickly, easier, and comfortably for all people. These systems predict the next most probable words and give users to choose of the needed word from these suggested words. Word prediction can help the writer by predicting the next word and helping complete the sentence correctly. This research aims to forecast the most suitable next word to complete a sentence for any given context. In this research, we have worked on the Bangla language. We have presented a process that can expect the next maximum probable and proper words and suggest a complete sentence using predicted words. In this research, GRU-based RNN has been used on the N-gram dataset to develop the proposed model. We collected a large dataset using multiple sources in the Bangla language and also compared it to the other approaches that have been used such as LSTM, and Naive Bayes. But this suggested approach provides excellent exactness than others. Here, the Unigram model provides 88.22%, Bi-gram model is 99.24%, Tri-gram model is 97.69%, and 4-gram and 5-gram models provide 99.43% and 99.78% on average accurateness. We think that our proposed method profound impression on Bangla search engines.

关键词： Bangla Language Words Prediction Sentence Completion GRU RNN Corpus N-Gram

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Photonic Crystal Fiber Based Sensor for Detecting Binary Liquid Mixture

引用

Optics and Photonics Journal 2017年第11期7卷 221-234页

作者： Md. Faizul Huq Arif Md. Jaminul Haque Biddut Md. Shaiful Islam Babu H M Mostafizur Rahman Md. Mahbubur Rahman busrat jahan Moshrefa Sultana Chaity Shah Mostafa Khaled Institute of Information Technology (IIT) University of Dhaka Dhaka Bangladesh Automation and Robotics Faculty of Electrical Engineering and Information Technology (EEIT) TU Dortmund University Dortmund Germany Department of Computer Science and Engineering World University of Bangladesh Dhaka Bangladesh School of Information Technology BAC International Study Centre Dhaka Bangladesh Department of Computer Science and Engineering Feni University Feni Bangladesh Institute of Information Technology (IIT) Jahangirnagar University Dhaka Bangladesh

Detection of liquid mixture of different volume ratio is very important in industrial purposes. The paper reports a sensing mechanism of binary liquid mixture for different volume fraction, based on the measurement of refractive index of the mixture. Here, a highly sensitive liquid filled core Photonic Crystal Fiber structure has been proposed to detect liquid mixture solution. Numerical investigation of the proposed structure is carried out by employing full vectorial Finite Element Method (FEM).

关键词： Binary Liquid Mixture Photonic Crystal Fiber Refractive Index Sensitivity Confinement Loss

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：