Generation of trustworthy attribute knowledge graph based on semantic analysis

Jia Wang; Xuejun Yu

doi:10.1117/12.3004232

11 October 2023 Generation of trustworthy attribute knowledge graph based on semantic analysis

Jia Wang, Xuejun Yu

Proceedings Volume 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023); 128004C (2023) https://doi.org/10.1117/12.3004232
Event: 6th International Conference on Computer Information Science and Application Technology (CISAT 2023), 2023, Hangzhou, China

Abstract

At present, with the rapid development of Internet information technology, the demand for enterprise-level intelligent information technology software projects has emerged in large numbers. Software trustworthiness has become an important part of the development of the software industry that cannot be ignored. For developers, software trustworthiness should be considered as an important factor from software development to the end. Software trustworthiness exists in the whole life cycle of software, at present, there is no trustworthy declaration document that can be applied in the whole development process of software, which makes it necessary for developers to repeatedly define trustworthy declaration documents in the process of developing information technology projects with the same functional attributes. Based on the above existing problems, this study takes the front and back ends of web and WeChat applets as the research objects. By obtaining the functional requirement documents of informatization projects as the data base, introducing natural language processing technology, constructing a semantic analysis model conforming to this study through semantic analysis processing technology, and finally realizing the function of automatically generating trustworthy behavior declaration files by traversing the language under the graph computing framework. In this thesis, we focus on the functional attribute extraction method based on semantic analysis technology and the knowledge graph generation and storage method of functional attribute keywords and high-frequency words, which lay the foundation for the automatic generation of trustworthy behavior statement documents afterwards.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jia Wang and Xuejun Yu "Generation of trustworthy attribute knowledge graph based on semantic analysis", Proc. SPIE 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023), 128004C (11 October 2023); https://doi.org/10.1117/12.3004232

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KEYWORDS

Semantics

Databases

Software development

Analytical research

Information technology

Data modeling

Data processing

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