Search "+Home -Bookshelf +Funny things +Alan Moore +YY +Sociology -Donald Knuth +Probability Theory: The Logic of Science +Math +David MacKay +Science of science +Science +Scientometrics +Books +Evolution of science +Web of Science +Scientific consensus +Information theory +Word embedding +Text analysis -word2vec"

Positive matches

• 0.054 + - Lexical feature selection
• 0.045 + - Migration
• 0.039 + - Interdisciplinary research
• 0.026 + - Industry-Academic Partnership
• 0.025 + - Data analysis
• 0.024 + - Paper/Nielsen2017
• 0.024 + - Probability theory
• 0.021 + - Policy
• 0.020 + - Sentence embedding
• 0.016 + - Paper/MacKay1991
• 0.014 + - Graph embedding
• 0.010 + - Natural language processing
• 0.010 + - Science policy
• 0.009 + - Continuous embedding
• 0.007 + - Software engineering in research
• 0.007 + - Pointwise mutual information
• 0.007 + - Paper/Tshitoyan2019unsupervised
• 0.007 + - Peer review
• 0.007 + - Scientific communication
• 0.007 + - Information Theory, Inference, and Learning Algorithms

Negative matches

• 0.024 + - G. Dobínski
• 0.006 + - Softmax function
• 0.003 + - Softmax
• 0.002 + - Gender bias
• 0.002 + - Paper/Hamilton2016
• 0.002 + - Paper/Levy2014a
• 0.002 + - Paper/Levy2014
• 0.002 + - WordRank
• 0.002 + - wiki2vec
• 0.002 + - Clinical concept embedding
• 0.002 + - Skip-gram
• 0.002 + - Hierarchical softmax
• 0.002 + - Paper/Perozzi2014
• 0.002 + - Chris McCormick
• 0.002 + - sense2vec
• 0.002 + - Neural network
• 0.002 + - Tomas Mikolov
• 0.002 + - TensorFlow
• 0.002 + - Sentiment analysis
• 0.001 + - Ilya Sutskever