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Design and Development of Knowledge Graph for Industrial Chain Based on Deep Learning.

Authors :
Li, Yue
Lei, Yutian
Yan, Yiting
Yin, Chang
Zhang, Jiale
Source :
Electronics (2079-9292); Apr2024, Vol. 13 Issue 8, p1539, 17p
Publication Year :
2024

Abstract

This paper aims to structure and semantically describe the information within the industrial chain by constructing an Industry Chain Knowledge Graph (ICKG), enabling more efficient and intelligent information management and analysis. In more detail, this paper constructs a multi-domain industrial chain dataset and proposes a method that combines the top-down establishment of a semantic expression framework with the bottom-up establishment of a data layer to build an ICKG. In the data layer, a deep learning algorithm based on BERT-BiLSTM-CRF is used to extract industry chain entities from relevant literature and reports. The results indicate that the model can effectively identify industry chain entities. These entities and relationships populate a Neo4j graph database, creating a large-scale ICKG for visual display and aiding cross-domain applications. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20799292
Volume :
13
Issue :
8
Database :
Complementary Index
Journal :
Electronics (2079-9292)
Publication Type :
Academic Journal
Accession number :
176902043
Full Text :
https://doi.org/10.3390/electronics13081539