Author:
Zhang Qianqian,Geng Guining,Tu Qun
Abstract
Technological innovation is vital for the survival and development of enterprises. In the era of intelligent information interconnection and knowledge-driven economy, there is a growing interest in how to manage high-volume data, unlock its potential value, and provide intelligent analysis and decision-making support for enterprise’s technological innovation. This paper proposes an improved knowledge association analysis method based on the semantic concept model. This approach enables the discovery of potential correlations and interaction modes between the influencing factors of enterprise’s technological innovation, and provides a useful reference for decision-making by combining the analysis with the enterprise’s own situation.
Publisher
Agora University of Oradea
Subject
Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications
Cited by
2 articles.
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