A Survey of Text Representation Methods and Their Genealogy

In recent years, with the advent of highly scalable artificial-neural-network-based text representation methods field natural language processing has seen unprecedented growth and sophistication. It become possible to distill complex linguistic information into multidimensional dense numeric vectors use distributional hypothesis. As a consequence, have been evolving at such quick pace that research community is struggling retain knowledge their interrelations. We contribute threefold this lack compilation, composition, systematization by providing survey current approaches, arranging them in genealogy, conceptualizing taxonomy examine explain state-of-the-art. Our valuable guide reference for artificial intelligence researchers practitioners interested applications as recommender systems, chatbots, sentiment analysis.