Search "+KenLM -RNN"

Positive matches

• 0.487 + - Natural language processing
• 0.088 + - NLP
• 0.071 + - Biomedical natural language processing
• 0.053 + - spaCy
• 0.052 + - CNN
• 0.037 + - Convolutional neural network
• 0.028 + - scispaCy
• 0.025 + - StanfordNLP
• 0.020 + - Lexical feature selection
• 0.019 + - Residual Learning
• 0.007 + - Text analysis
• 0.006 + - Pointwise mutual information
• 0.006 + - Generative adversarial networks
• 0.005 + - Computational creativity
• 0.005 + - Residual leanrning
• 0.004 + - Gradient descent
• 0.003 + - Dropout
• 0.003 + - Brain and deep learning
• 0.002 + - Archetype
• 0.002 + - Artificial neural network

Negative matches

• 0.483 + - Recurrent neural network
• 0.011 + - Attention (Deep learning)
• 0.006 + - String metric
• 0.006 + - Keras
• 0.006 + - Paper/Hochreiter1997
• 0.006 + - NLTK
• 0.006 + - Word segmentation
• 0.006 + - Latent Dirichlet allocation
• 0.006 + - Paper/Bahdanau2015
• 0.006 + - Paper/Cooijmans2016
• 0.006 + - BookNLP
• 0.006 + - Christopher D. Manning
• 0.006 + - KoNLPy
• 0.006 + - Topic modeling
• 0.006 + - Sentence embedding
• 0.006 + - TensorFlow
• 0.005 + - Sentiment analysis
• 0.003 + - tf-idf
• 0.003 + - Paper
• 0.003 + - Ilya Sutskever