Extracting entity relations for “problem-solving” knowledge graph of scientific domains using word analogy
Aslib Journal of Information Management
ISSN: 2050-3806
Article publication date: 8 June 2022
Issue publication date: 19 June 2023
Abstract
Purpose
Problem-solving” is the most crucial key insight of scientific research. This study focuses on constructing the “problem-solving” knowledge graph of scientific domains by extracting four entity relation types: problem-solving, problem hierarchy, solution hierarchy and association.
Design/methodology/approach
This paper presents a low-cost method for identifying these relationships in scientific papers based on word analogy. The problem-solving and hierarchical relations are represented as offset vectors of the head and tail entities and then classified by referencing a small set of predefined entity relations.
Findings
This paper presents an experiment with artificial intelligence papers from the Web of Science and achieved good performance. The F1 scores of entity relation types problem hierarchy, problem-solving and solution hierarchy, which were 0.823, 0.815 and 0.748, respectively. This paper used computer vision as an example to demonstrate the application of the extracted relations in constructing domain knowledge graphs and revealing historical research trends.
Originality/value
This paper uses an approach that is highly efficient and has a good generalization ability. Instead of relying on a large-scale manually annotated corpus, it only requires a small set of entity relations that can be easily extracted from external knowledge resources.
Keywords
Acknowledgements
This study is supported by the MOE (Ministry of Education in China) Project of Humanities and Social Sciences (No. 21YJC870003); and the Jiangsu Provincial Social Science Foundation of China (No. 21TQC002).
Citation
Chen, G., Peng, J., Xu, T. and Xiao, L. (2023), "Extracting entity relations for “problem-solving” knowledge graph of scientific domains using word analogy", Aslib Journal of Information Management, Vol. 75 No. 3, pp. 481-499. https://doi.org/10.1108/AJIM-03-2022-0129
Publisher
:Emerald Publishing Limited
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