Applying NLP: Use Cases of Natural Language Processing in Commercial Applications
My presentation will look at how companies are applying NLP, the impact of deep learning on performance and methodology, then a deep dive on an automotive use case leveraging chat bot transcripts for regulatory reporting.
performance relative to training data size is task dependent • 5,000 annotated customer complaints for training and validation data • Possible to leverage other resources to overcome data sparsity issues using transfer learning
softmax output layer for multi-class classifcation • Trained custom word embeddings for the automotive domain with an unsupervised model • Framework in place for transfer learning for data sparsity issues For a more in depth look, read Yoon Kim’s paper “Convolutional Neural Networks for Sentence Classifcation”