Mechanisms and Paths for Constructing the Organic Interface between Digital Economy and Chinese-Style Modernization Based on Cognitive Mapping

Abstract

In the process of China’s modernization, the organic articulation of the digital economy provides key support. This paper explores the articulation network paradigm of both and proposes a method for building cognitive mapping on a complex network. For the digital modernization industry, the vector representation encoding is completed by using the multi-granularity representation of this paper, and an N-gram encoder realizes the industry entity recognition. A basic idea of relationship template annotation is developed for recognizing entities, and the relationship extraction framework includes three parts: representation learning of templates, quality assessment of templates, and relationship classification model based on template quality. The regression results of the three major economic regions, namely, the eastern region, the central region and the western region, show that the level of digital economy development in the region has a more significant positive effect on the structure of manufacturing output value. The largest regression coefficient is 3.3044 for the eastern region, while the central, western and northeastern regions are 1.85567, 2.45457, and -0.13798, respectively. Through the study of cognitive mapping, the study provides an effective paradigm for Chinese-style modernization.

Keywords

• cognitive mapping
• vector representation coding
• entity recognition
• relationship extraction
• n-gram encoder
• digital economy
• 93c62