- More semantic user-interaction with the text data, eg.: understand natural language user queries better and formulate synthesized answers.
- concept inception –> form –> concept extraction
- idea-class versus form-instance
- simple user-language for creating concept queries
- semantic sentence embedding encoding-decoding:
- demo: semantic book search
- NLP meaning visualizations:
- embeddings (“mapping from discrete objects, such as words, to vectors of real numbers”):