Question answer system based on natural language understanding

被引:0
|
作者
Guo, Qing-Lin [1 ,2 ]
Fan, Xiao-Zhong [2 ]
机构
[1] Dept. of Computer Science, North China Electric Power University, Beijing 102206, China
[2] Dept. of Computer Science, Beijing Institute of Technology, Beijing 100081, China
关键词
Formal languages - Formal logic - Internet - Semantics;
D O I
暂无
中图分类号
学科分类号
摘要
Automatic Question Answer System (QAS) is a kind of high-powered software system based on Internet. Its key technology is the interrelated technology based on natural language understanding, including the construction of knowledge base and corpus, the Word Segmentation and POS Tagging of text, the Grammatical Analysis and Semantic Analysis of sentences etc. This thesis dissertated mainly the denotation of knowledge-information based on semantic network in QAS, the stochastic syntax-parse model named LSF of knowledge-information in QAS, the structure and constitution of QAS. And the LSF models parameters were exercised, which proved that they were feasible. At the same time, through the limited-domain QAS which was exploited for banks by us, these technologies were proved effective and propagable.
引用
收藏
页码:419 / 422
相关论文
共 50 条
  • [1] The question answer system based on natural language understanding
    郭庆琳
    樊孝忠
    Journal of Harbin Institute of Technology, 2007, (03) : 419 - 422
  • [2] QUESTION-ANSWER SYSTEM WHICH REPRODUCES INFORMATION IN A NORMALIZED NATURAL-LANGUAGE
    LITVINTSEVA, LV
    ENGINEERING CYBERNETICS, 1977, 15 (02): : 36 - 43
  • [3] Natural Language Question and Answer Method for RDF Information Resource
    Akita, Chie
    Mase, Motohiro
    Kitamura, Yasuhiko
    2009 IEEE/WIC/ACM INTERNATIONAL JOINT CONFERENCES ON WEB INTELLIGENCE (WI) AND INTELLIGENT AGENT TECHNOLOGIES (IAT), VOL 3, 2009, : 22 - +
  • [4] Developing a Knowledge Graph for a Question Answering System to Answer Natural Language Questions on German Grammar
    Falke, Stefan
    SEMANTIC WEB: ESWC 2019 SATELLITE EVENTS, 2019, 11762 : 199 - 208
  • [5] Multi-purposed Question Answer Generator with Natural Language Processing
    Desai, Hiral
    Sheikh, Mohammed Firdos Alam
    Sharma, Satyendra K.
    EMERGING TRENDS IN EXPERT APPLICATIONS AND SECURITY, 2019, 841 : 139 - 145
  • [6] Reliable Natural Language Understanding with Large Language Models and Answer Set Programming
    Rajasekharan, Abhiramon
    Zeng, Yankai
    Padalkar, Parth
    Gupta, Gopal
    ELECTRONIC PROCEEDINGS IN THEORETICAL COMPUTER SCIENCE, 2023, (385): : 274 - 287
  • [7] Reliable Natural Language Understanding with Large Language Models and Answer Set Programming
    Rajasekharan, Abhiramon
    Zeng, Yankai
    Padalkar, Parth
    Gupta, Gopal
    Electronic Proceedings in Theoretical Computer Science, EPTCS, 2023, 385 : 274 - 287
  • [8] Generating Natural Language Question-Answer Pairs from a Knowledge Graph Using a RNN Based Question Generation Model
    Indurthi, Sathish
    Raghu, Dinesh
    Khapra, Mitesh M.
    Joshi, Sachindra
    15TH CONFERENCE OF THE EUROPEAN CHAPTER OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (EACL 2017), VOL 1: LONG PAPERS, 2017, : 376 - 385
  • [9] A chatbot based question and answer system for the auxiliary diagnosis of chronic diseases based on large language model
    Zhang, Sainan
    Song, Jisung
    SCIENTIFIC REPORTS, 2024, 14 (01):
  • [10] Answer planning based answer generation for cooking question answering system
    Xia, Ling, 1600, Journal of Chemical and Pharmaceutical Research, 3/668 Malviya Nagar, Jaipur, Rajasthan, India (06):