Research on Computer Intelligent ChatGPT Natural Language Processing System Based on Scientific Knowledge Graph

被引：0
|
作者：
Zhan, Liuchun [1 ,2 ]
Huang, Changjiang [1 ,2 ]
机构：
[1] Guangzhou Coll Appl Sci & Technol, Coll Comp Sci, Guangzhou, Peoples R China
[2] Guangzhou Coll Appl Sci & Technol, Res Base Guangdong Social Sci Federat Urban & Rur, Guangzhou, Peoples R China
来源：
PROCEEDINGS OF 2024 INTERNATIONAL CONFERENCE ON MACHINE INTELLIGENCE AND DIGITAL APPLICATIONS, MIDA2024 | 2024年
关键词：
Software knowledge graph; ChatGPT; Software knowledge extraction; Natural language processing system;
D O I：
10.1145/3662739.3664740
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A synonym mining method is proposed by combining the character vector graph and noise robust learning method. The model uses paired word vectors pre-trained by ChatGPT to enhance entity semantic representation. Classify marks with noise. Then the cross optimal processing is carried out to identify the true and false marks. The two-layer construction system of knowledge extraction and knowledge fusion is constructed to realize the independent construction and answer of software engineering questions. The system effectively improves the efficiency of software project understanding and software reuse.
引用
收藏
页码：47 / 51
页数：5
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