To read this content please select one of the options below:

A novel word-graph-based query rewriting method for question answering

Rongen Yan (School of Artificial Intelligence, Beijing Normal University, Beijing, China)
Depeng Dang (School of Artificial Intelligence, Beijing Normal University, Beijing, China)
Hu Gao (School of Artificial Intelligence, Beijing Normal University, Beijing, China)
Yan Wu (School of Artificial Intelligence, Beijing Normal University, Beijing, China)
Wenhui Yu (School of Artificial Intelligence, Beijing Normal University, Beijing, China)

Data Technologies and Applications

ISSN: 2514-9288

Article publication date: 18 May 2023

Issue publication date: 29 January 2024

167

Abstract

Purpose

Question answering (QA) answers the questions asked by people in the form of natural language. In the QA, due to the subjectivity of users, the questions they query have different expressions, which increases the difficulty of text retrieval. Therefore, the purpose of this paper is to explore new query rewriting method for QA that integrates multiple related questions (RQs) to form an optimal question. Moreover, it is important to generate a new dataset of the original query (OQ) with multiple RQs.

Design/methodology/approach

This study collects a new dataset SQuAD_extend by crawling the QA community and uses word-graph to model the collected OQs. Next, Beam search finds the best path to get the best question. To deeply represent the features of the question, pretrained model BERT is used to model sentences.

Findings

The experimental results show three outstanding findings. (1) The quality of the answers is better after adding the RQs of the OQs. (2) The word-graph that is used to model the problem and choose the optimal path is conducive to finding the best question. (3) Finally, BERT can deeply characterize the semantics of the exact problem.

Originality/value

The proposed method can use word-graph to construct multiple questions and select the optimal path for rewriting the question, and the quality of answers is better than the baseline. In practice, the research results can help guide users to clarify their query intentions and finally achieve the best answer.

Keywords

Acknowledgements

Funding: This research is supported by The National Key Research and Development Program of China under grant no. 2020YFC1523303; The Key Research and Development Program of Qinghai Province under grant no. 2020-SF-140; the National Natural Science Foundation of China under grant nos. 61672102, 61073034, 61370064 and 60940032; the National Social Science Foundation of China under grant no. BCA150050; the Program for New Century Excellent Talents in the University of Ministry of Education of China under grant no. NCET-10-0239; the Open Project Sponsor of Beijing Key Laboratory of Intelligent Communication Software and Multimedia under grant no. ITSM201493 and the Science Foundation of Ministry of Education of China and China Mobile Communications Corporation under grant no. MCM20130371.

Conflicts of interest. None.

Citation

Yan, R., Dang, D., Gao, H., Wu, Y. and Yu, W. (2024), "A novel word-graph-based query rewriting method for question answering", Data Technologies and Applications, Vol. 58 No. 1, pp. 1-23. https://doi.org/10.1108/DTA-05-2022-0187

Publisher

:

Emerald Publishing Limited

Copyright © 2023, Emerald Publishing Limited

Related articles