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Positive matches

• 0.040 + - Interdisciplinary research
• 0.024 + - Industry-Academic Partnership
• 0.017 + - Natural language processing
• 0.017 + - Public health policy
• 0.017 + - Lasswell's maxim
• 0.017 + - Probability theory
• 0.016 + - Text analysis
• 0.015 + - Sentence embedding
• 0.014 + - Continuous embedding
• 0.013 + - Pointwise mutual information
• 0.012 + - Research funding
• 0.011 + - Paper/MacKay1991
• 0.009 + - PyTorch-BigGraph
• 0.009 + - GraphSAGE
• 0.008 + - tf-idf
• 0.008 + - Collaborative software
• 0.007 + - Data mining
• 0.005 + - Software engineering in research
• 0.005 + - Software engineering
• 0.005 + - Paper/Tshitoyan2019unsupervised

Negative matches

• 0.003 + - Softmax function
• 0.002 + - Neuron
• 0.001 + - Neural network
• 0.001 + - Clinical concept embedding
• 0.001 + - Paper/Perozzi2014
• 0.001 + - Paper/Hamilton2016
• 0.001 + - tfidf
• 0.001 + - Gender bias
• 0.001 + - Skip-gram
• 0.001 + - Chris McCormick
• 0.001 + - Ilya Sutskever
• 0.001 + - WordRank
• 0.001 + - Paper/Levy2014
• 0.001 + - sense2vec
• 0.001 + - Paper/Levy2014a
• 0.001 + - wiki2vec
• 0.001 + - Softmax
• 0.001 + - Brain and deep learning
• 0.001 + - Artificial neural network
• 0.001 + - Deep learning