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Positive matches
- 0.038 + - Probability
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- 0.017 + - Lasswell's maxim
- 0.017 + - Paper/Nielsen2017
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- 0.013 + - Pointwise mutual information
- 0.011 + - Text analysis
- 0.011 + - Industry-Academic Partnership
- 0.011 + - Paper/MacKay1991
- 0.010 + - Data analysis
- 0.008 + - tf-idf
- 0.007 + - Sentence embedding
- 0.007 + - Natural language processing
- 0.007 + - Word embedding
- 0.005 + - Software engineering in research
- 0.005 + - Edwin Thompson Jaynes
- 0.005 + - Machine learning
- 0.005 + - Probability distribution
- 0.005 + - Cross entropy
- 0.004 + - NLP
Negative matches
- 0.008 + - PyTorch-BigGraph
- 0.008 + - GraphSAGE
- 0.007 + - Continuous embedding
- 0.004 + - Hierarchical softmax
- 0.003 + - Network geometry
- 0.001 + - Embedded topic model
- 0.000 + - Gender bias
- 0.000 + - Paper/Tshitoyan2019unsupervised
- 0.000 + - Deep learning
- 0.000 + - Paper/Hamilton2016
- 0.000 + - Tomas Mikolov
- 0.000 + - Paper/Levy2014a
- 0.000 + - WordRank
- 0.000 + - Clinical concept embedding
- 0.000 + - Paper/Levy2014
- 0.000 + - Ilya Sutskever
- 0.000 + - TensorFlow
- 0.000 + - Topic model
- 0.000 + - Topic mapping
- 0.000 + - Archetype