- CNN or LSTM or any deep learning algorithm
- You can give few Keras implementation
Please have a look at this reference. It gives a practical example of learning to generate words in keras.
https://machinelearningmastery.com/text-generation-lstm-recurrent-neural-networks-python-keras/
Hello,
you can read :
Text Generation With LSTM Recurrent Neural Networks in Python with Keras
in https://machinelearningmastery.com/text-generation-lstm-recurrent-neural-networks-python-keras/
Updated example for Keras 2.0.2, TensorFlow 1.0.1 and Theano 0.9.0.
Good work
Not sure what you mean by 'combine CNN/LSTM with stemming', but if you have only limited training data but a reasonable stemmer, or a dictionary of stems, you could add input features to the network indicating the position of a stem (start and end) as recognized by the stemmer. This could give a boost in learning if the stemmer covers more cases than your training data, and still use the flexibility of the CNN/RNN's adaptability to new cases.
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