Search "+KenLM -StanfordNLP"

Positive matches

• 0.082 + - NLP
• 0.053 + - spaCy
• 0.053 + - Biomedical natural language processing
• 0.028 + - scispaCy
• 0.019 + - Residual Learning
• 0.014 + - Lexical feature selection
• 0.014 + - Convolutional neural network
• 0.006 + - Generative adversarial networks
• 0.005 + - Computational creativity
• 0.005 + - Residual leanrning
• 0.005 + - Recurrent neural network
• 0.004 + - Gradient descent
• 0.003 + - Dropout
• 0.003 + - Brain and deep learning
• 0.002 + - Archetype
• 0.002 + - Artificial neural network
• 0.002 + - Language
• 0.001 + - Theano
• 0.001 + - Attention (Deep learning)
• 0.001 + - Deep generative models

Negative matches

• 0.058 + - CNN
• 0.018 + - Text analysis
• 0.013 + - fastText
• 0.013 + - Latent Dirichlet allocation
• 0.013 + - BookNLP
• 0.013 + - KoNLPy
• 0.012 + - Sentence embedding
• 0.012 + - Christopher D. Manning
• 0.012 + - String metric
• 0.012 + - Kyunghyun Cho
• 0.012 + - NLTK
• 0.012 + - Word segmentation
• 0.011 + - Sentiment analysis
• 0.009 + - Machine learning
• 0.009 + - Machine translation
• 0.008 + - Deep learning
• 0.006 + - Tomas Mikolov
• 0.006 + - Keras
• 0.006 + - Differentiable neural computers
• 0.006 + - Paper/Hochreiter1997