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sumanismcse

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Using Long Short Term Memory Model and Recursive Neural Network for Sentiment Analysis to use in the automated therapeutic app as an input to read intent of user in Google's cloud natural language processing service 'dialogflow' and on that basis we provide low cost therapy

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For this problem, we proposed the use of bidirectional-LSTM’s(Long Short Term Memory) with 1-D CNN layer to classify patient notes at character level and at word level. The 1-D CNN is employed to scale back the training time. In order to improve the performance, we will also feed the network combined word embedding consisting of Pre-trained word2vec 100 dimension word embedding trained on the Twitter ADR Dataset database and character embedding generated by a Char-CNN for Named Entity Recognition