Understanding hierarchical structural evolution in a scientific discipline: A case study of artificial intelligence

Volume: 14, Issue: 3, Pages: 101047 - 101047
Published: Aug 1, 2020
Abstract
Detecting what type of knowledge constitutes a discipline, tracking how the knowledge changes, and understanding why the changes are triggered are the key issues in analyzing scientific development from a macro perspective, which is usually analyzed by the topic of evolution. However, traditional methods assume that the disciplinary structure is flat with only one-layer topics, rather than a tree-like structure with hierarchical topics, which...
Paper Details
Title
Understanding hierarchical structural evolution in a scientific discipline: A case study of artificial intelligence
Published Date
Aug 1, 2020
Volume
14
Issue
3
Pages
101047 - 101047
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