Min Song
Computer Vision and Pattern Recognition · 2019
A researcher in the Science corpus: 1 paper; trusts 17 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 6 citations into it
- Statistics and Probability — 6 citations into it
- Artificial Intelligence — 5 citations into it
- Molecular Biology — 5 citations into it
Whom Min Song trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Chaomei Chen
- Nees Jan van Eck
- Christopher Kullenberg
- Robin Haunschild
- Chengliang Zhang
- Tomas Mikolov
- T. Landauer
- Ludo Waltman
- Dick Kasperowski
- Eugene Garfield
Papers from Min Song's perspective
Ordered by how strongly the researchers Min Song trusts endorse each paper. Same corpus, a different order for every researcher.
- Searching for intellectual turning points: Progressive knowledge domain visualization (Proceedings of the National Academy of Sciences of the United States of America)
- Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
- WordNet: A Lexical Database for English
- Emerging trends in regenerative medicine: a scientometric analysis in CiteSpace (Expert Opinion on Biological Therapy)
- From the science of science to Scientometrics visualizing the history of science with HistCite software (J. Informetrics)
- Fish Oil, Raynaud's Syndrome, and Undiscovered Public Knowledge (Perspectives in biology and medicine)
- The structure and dynamics of cocitation clusters: A multiple-perspective cocitation analysis (J. Assoc. Inf. Sci. Technol.)
- Software survey: VOSviewer, a computer program for bibliometric mapping (Scientometrics)
- An overview of MetaMap: historical perspective and recent advances (J. Am. Medical Informatics Assoc.)
- Predictive effects of structural variation on citation counts (J. Assoc. Inf. Sci. Technol.)
Their papers
- Visualizing a field of research: A methodology of systematic scientometric reviews (2019) — 1,250 citations