The influence of semantic link network on the ability of question-answering system

Abstract

Semantic Link Network plays an important role in representing and understanding text. This paper investigates the influence of semantic links on the basic abilities of a type of QA system that extracts answers from a range of texts (answer range). Research concerns how semantic links influence the answer range and the performance of this type of QA system. Research also concerns the ability to answering different types of questions and supporting different patterns of answering questions. Based on the semantic link network extracted from Wikipedia, an experimental QA system is developed to answer questions according to a range of pages in Wikipedia. Research reached the following results: (1) the answer range and the semantic link network influence each other: keeping a certain range of performance, increase one can decrease the request of the other; and, (2) the semantic link network can enhance the ability of QA system in answering questions and supporting patterns of answering questions covered by semantic link network.

Publication DOI: https://doi.org/10.1016/j.future.2020.02.042
Funding Information: Research was supported by the National Science Foundation of China (No. 61640212 , 61602256 , 61876048 , 61806101 ) and supported by the International Research Network on Cyber–Physical–Social Intelligence, China consisting of Guangzhou University, Aston
Additional Information: © 2020, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Uncontrolled Keywords: Performance of question answering system,Question answering system,Semantic link network,Software,Hardware and Architecture,Computer Networks and Communications
Publication ISSN: 1872-7115
Last Modified: 04 Mar 2024 08:38
Date Deposited: 13 Mar 2020 09:26
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
https://www.sci ... 6127?via%3Dihub (Publisher URL)
PURE Output Type: Article
Published Date: 2020-07
Published Online Date: 2020-02-19
Accepted Date: 2020-02-16
Authors: Xu, Bei
Zhuge, Hai (ORCID Profile 0000-0001-8250-6408)

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