Abstract

At present, major search engines emerge in endlessly, and the pop-up result list of search keywords makes people dizzy. In order to improve this problem and make the question query more concise and convenient, this article is based on the DuReader data set and reproduces BiDAF (Bi-Directional Attention Flow) The model builds an intelligent question answering system in the open field. The final model can extract answers to questions more accurately after training. This article embeds deep learning technology into the system and uses intelligent chat to show them.

Details

Title
Research and Implementation of Open Domain Question Answering System Based on DuReader Dataset and BIDAF Model
Author
Guo, Zechen 1 ; Wan, Fucheng 1 ; Ma, Ning 1 

 Key Laboratory of China’s Ethnic Languages and Information Technology of Ministry of Education, Northwest Minzu University, Lanzhou, Gansu 730000, China; Key Laboratory of China’s Ethnic Languages and Intelligent Processing of Gansu Province, Northwest Minzu University, Lanzhou, Gansu 730000, China 
Publication year
2021
Publication date
Jan 2021
Publisher
IOP Publishing
ISSN
17426588
e-ISSN
17426596
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2512953018
Copyright
© 2021. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.