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General Information
Editor-in-chief

Prof. Pascal Lorenz
University of Haute Alsace, France
 
It is my honor to be the editor-in-chief of IJFCC. The journal publishes good papers in the field of future computer and communication. Hopefully, IJFCC will become a recognized journal among the readers in the filed of future computer and communication.

IJFCC 2020 Vol.9(3): 52-56 ISSN: 2010-3751
DOI: 10.18178/ijfcc.2020.9.3.565

End-To-End Neural Network for Paraphrased Question Answering Architecture with Single Supporting Line in Bangla Language

Md. Mohsin Uddin, Nazmus Sakib Patwary, Md. Mohaiminul Hasan, Tanvir Rahman, and Mir Tanveer Islam
Abstract—Recent studies on QA (Question Answering) system in English language have been emerged extensively with the composition of Natural Language Processing (NLP) and Information Retrieval (IR) by amplifying miniature sub tasks to accomplish a whole AI-system having capability of answering and reasoning complicated and long questions through understating paragraph. In our proposed study, we present a general heuristic framework, an end-to-end model used for paraphrased question answering using single supporting line which is the initial appearance ever in Bangla language. Corpus dataset was scrapped from Bangla wiki and then questions were generated corresponding context have been used to learn the model. Translated bAbI dataset (1 supporting fact) in Bangla language has been also incorporated with to experiment the proposed model manually. To predict appropriate answer, model is trained with question-answer pair and a supporting line. For comparing our task applying variation of basic Recurrent Neural Network (RNN): Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) different accuracy has been found. For further accomplishment, synthetic and semantic word relevance in high dimension vector space: Bangla word embedding system(word2vec) is added to the system as sentence representation along with Positioning Encoding (PE) and which outperforms both memory network GRU and LSTM precisely.

Index Terms—Machine learning, natural language processing, information retrieval, long short time memory, gated recurrent unit.

Md. Mohsin Uddin is with East West University, Dhaka Bangladesh, (e-mail: mmuddin@ewubd.edu).
Nazmus Sakib Patwary, Md. Mohaiminul Hasan, and Tanvir Rahman were with East West University, Dhaka, Bangladesh (e-mail: nazmus.ewu@gmail.com, mohaiminul.hasan.ewu@gmail.com, tanvir.rahman.ewu@gmail.com).
Mir Tanveer Islam completed his BS in EEE from North South University, Dhaka, Bangladesh (e-mail: mirtanveerislam@Gmail.com).

[PDF]

Cite: Md. Mohsin Uddin, Nazmus Sakib Patwary, Md. Mohaiminul Hasan, Tanvir Rahman, and Mir Tanveer Islam, "End-To-End Neural Network for Paraphrased Question Answering Architecture with Single Supporting Line in Bangla Language," International Journal of Future Computer and Communication vol. 9, no. 3, pp. 52-56, 2020.

Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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