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Human and Machine Intelligence: Building The Future Of Text Analytics

Text analytics draws on multiple techniques from simple string matching to deeper statistical analyses. Recently, Deep Learning (DL) has emerged as a compelling approach to address many common use-cases including Named Entity Recognition (NER), document classification and relationship extraction. Novel algorithms including Word2Vec, ELMo, BERT, XLNet and ERNIE released by acknowledged sources, represent a step-change in machine-understanding of human-written text.