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Positive matches
- 0.031 + - Interdisciplinary research
- 0.019 + - Industry-Academic Partnership
- 0.019 + - Continuous embedding
- 0.018 + - Edwin Thompson Jaynes
- 0.017 + - Sentence embedding
- 0.015 + - Information theory
- 0.014 + - Policy
- 0.013 + - GraphSAGE
- 0.013 + - PyTorch-BigGraph
- 0.011 + - Hessian matrix
- 0.011 + - Paper
- 0.009 + - Natural language processing
- 0.008 + - Peer review
- 0.007 + - Scientific communication
- 0.007 + - Paper/Tshitoyan2019unsupervised
- 0.007 + - Bibliometrics
- 0.007 + - Science policy
- 0.007 + - Author name disambiguation
- 0.006 + - Stochastic process
- 0.006 + - Probability
Negative matches
- 0.003 + - Softmax function
- 0.002 + - Sentiment analysis
- 0.002 + - tf-idf
- 0.002 + - Softmax
- 0.002 + - Gender bias
- 0.002 + - Paper/Hamilton2016
- 0.002 + - Clinical concept embedding
- 0.002 + - Gensim
- 0.002 + - Neural network
- 0.002 + - Paper/Perozzi2014
- 0.002 + - sense2vec
- 0.002 + - Paper/Levy2014
- 0.002 + - Chris McCormick
- 0.001 + - Deep learning
- 0.001 + - Hierarchical softmax
- 0.001 + - Paper/Levy2014a
- 0.001 + - WordRank
- 0.001 + - wiki2vec
- 0.001 + - Ilya Sutskever
- 0.001 + - Finkbeiner test