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Positive matches

• 0.228 + - Machine learning
• 0.039 + - Books
• 0.036 + - Home
• 0.025 + - Gradient descent
• 0.022 + - Recommender system
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• 0.015 + - Random forest
• 0.012 + - Boosting (machine learning)
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• 0.011 + - Interdisciplinary research
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• 0.010 + - skorch
• 0.009 + - Tim Hopper
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• 0.007 + - Privacy and Deanonymization
• 0.007 + - Future of work

Negative matches

• 0.028 + - Text analysis
• 0.014 + - NLTK
• 0.014 + - Gensim
• 0.010 + - Pointwise mutual information
• 0.009 + - Lexical feature selection
• 0.005 + - Natural language processing
• 0.003 + - Data analysis
• 0.001 + - sense2vec
• 0.001 + - Skip-gram
• 0.001 + - Paper/Perozzi2014
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• 0.001 + - Convolutional neural network
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• 0.001 + - scispaCy
• 0.001 + - GloVe
• 0.000 + - StanfordNLP
• 0.000 + - Clinical concept embedding
• 0.000 + - Probability
• 0.000 + - word2vec
• 0.000 + - TensorFlow