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Positive matches

• 0.045 + - Interdisciplinary research
• 0.025 + - Probability theory
• 0.022 + - Word embedding
• 0.020 + - Natural language processing
• 0.019 + - Probability
• 0.017 + - Migration
• 0.014 + - Policy
• 0.012 + - Science policy
• 0.012 + - Continuous embedding
• 0.011 + - Literary allusions in science
• 0.010 + - Sure Thing hypothesis
• 0.009 + - Paper
• 0.009 + - PyTorch-BigGraph
• 0.008 + - Network science
• 0.007 + - Teaching
• 0.007 + - Jeannette M. Wing
• 0.007 + - Larry Wasserman
• 0.007 + - Julia Silge
• 0.007 + - Paper/Huang2019historical
• 0.007 + - Paper/Nielsen2017

Negative matches

• 0.022 + - Lexical feature selection
• 0.004 + - Kullback–Leibler divergence
• 0.004 + - Machine learning
• 0.004 + - Cross entropy
• 0.004 + - Gibbs' inequality
• 0.004 + - David Feldman
• 0.004 + - Pointwise mutual information
• 0.004 + - Information Theory, Inference, and Learning Algorithms
• 0.001 + - Text analysis
• 0.001 + - Class imbalance
• 0.001 + - Automated machine learning
• 0.001 + - Future of work
• 0.001 + - Class imbalance problem
• 0.001 + - scikit-learn
• 0.001 + - Recommender system
• 0.000 + - Gradient descent
• 0.000 + - Regular expression
• 0.000 + - Social network
• 0.000 + - Pathogen transmission
• 0.000 + - Paper/Gatys2015