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Positive matches

• 0.052 + - Network geometry
• 0.049 + - Graph embedding
• 0.025 + - Science policy
• 0.024 + - Probability
• 0.023 + - Topic model
• 0.022 + - word2vec
• 0.018 + - Industry-Academic Partnership
• 0.017 + - Harold Lasswell
• 0.017 + - Public health policy
• 0.015 + - Sentence embedding
• 0.015 + - Migration
• 0.011 + - Information theory
• 0.008 + - Hessian matrix
• 0.005 + - Paper/Tshitoyan2019unsupervised
• 0.005 + - Software engineering
• 0.005 + - Collaborative software
• 0.005 + - Stochastic process
• 0.005 + - Bayesian inference
• 0.005 + - Frequentist inference
• 0.005 + - Probability distribution

Negative matches

• 0.008 + - CNN
• 0.003 + - Residual Learning
• 0.002 + - Paper/Gatys2015
• 0.002 + - RNN
• 0.001 + - Residual leanrning
• 0.001 + - Text analysis
• 0.001 + - fastText
• 0.001 + - BERT
• 0.001 + - String metric
• 0.001 + - KenLM
• 0.001 + - Deep learning
• 0.001 + - NLTK
• 0.001 + - Word segmentation
• 0.001 + - Dialog act
• 0.001 + - BookNLP
• 0.001 + - Kyunghyun Cho
• 0.001 + - Christopher D. Manning
• 0.001 + - KoNLPy
• 0.001 + - Sentiment analysis
• 0.001 + - Recurrent neural network