Recognizing Core Knowledge From Domain Knowledge Network for Platform-Based Business Development

IF 4.5 2区计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS

IEEE Transactions on Computational Social Systems Pub Date : 2024-07-18 DOI:10.1109/TCSS.2024.3385671

Poly Z.H. Sun;Hongwei Jiang;Chengjun Wang;Xinfeng Ru;Xinguo Ming

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引用次数: 0

Abstract

As an emerging topic in industrial digital transformation, digital business development in the context of platformization has received widespread attention. A large number of industrial companies have established new platform-based systems for digital business development by integrating their original information systems. The unified platform development mode promotes the integration of previously decentralized knowledge. However, the massive expansion of the knowledge system under platformization causes it to be no easier for developers to master or understand the core knowledge (context, concepts, and elements) of the business to be developed. According to the above dilemmas we have observed in the industry, in this article, a domain knowledge network modeling method for the knowledge system under platformization and a GP-based rule generation method for recognizing core business knowledge in the domain knowledge network are proposed for the first time. Our experiment and practical case study verify that our method can recognize a set of core business knowledge from a large knowledge network efficiently, which could help developers understand the business to be developed with a lower cognitive load. We hope the idea of platform-based business development and core business knowledge recognition can provide a reference for those companies that need efficient digital business development.

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从领域知识网络中识别核心知识，促进基于平台的业务发展

作为工业数字化转型的新兴课题，平台化背景下的数字化业务发展受到了广泛关注。大量工业企业通过整合原有信息系统，建立了新的平台化系统，以实现数字化业务发展。统一的平台化发展模式促进了原有分散知识的整合。然而，平台化下知识体系的大量扩充导致开发人员难以掌握或理解待开发业务的核心知识（背景、概念和要素）。根据我们在业界观察到的上述困境，本文首次提出了平台化下知识体系的领域知识网络建模方法和基于 GP 的规则生成方法，用于识别领域知识网络中的核心业务知识。我们的实验和实际案例研究验证了我们的方法可以从一个庞大的知识网络中高效地识别出一组核心业务知识，从而帮助开发人员以较低的认知负荷理解待开发的业务。我们希望基于平台的业务开发和核心业务知识识别的理念能为那些需要高效数字业务开发的公司提供参考。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Computational Social Systems Social Sciences-Social Sciences (miscellaneous)

CiteScore

10.00

自引率

20.00%

发文量

316

期刊介绍： IEEE Transactions on Computational Social Systems focuses on such topics as modeling, simulation, analysis and understanding of social systems from the quantitative and/or computational perspective. "Systems" include man-man, man-machine and machine-machine organizations and adversarial situations as well as social media structures and their dynamics. More specifically, the proposed transactions publishes articles on modeling the dynamics of social systems, methodologies for incorporating and representing socio-cultural and behavioral aspects in computational modeling, analysis of social system behavior and structure, and paradigms for social systems modeling and simulation. The journal also features articles on social network dynamics, social intelligence and cognition, social systems design and architectures, socio-cultural modeling and representation, and computational behavior modeling, and their applications.