Mapping the physics research space: a machine learning approach

Mapping the physics research space: a machine learning approach

Abstract Scientific discoveries do not occur in vacuum but rather by connecting existing pieces of knowledge in new and creative ways. Mapping the relation and structure of scientific knowledge is therefore central to our understanding of the dynamics of scientific production. Here we introduce a ne...

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Bibliographic Details
Main Authors: Matteo Chinazzi, Bruno Gonçalves, Qian Zhang, Alessandro Vespignani
Format: Article
Language:English
Published: SpringerOpen 2019-11-01
Series:EPJ Data Science
Subjects:
Embeddings
Research space
Principle of relatedness
Fingerprinting scientific production
Revealed comparative advantage
Predicting research specialization
Online Access:http://link.springer.com/article/10.1140/epjds/s13688-019-0210-z

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http://link.springer.com/article/10.1140/epjds/s13688-019-0210-z

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