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Natural language processing (NLP) is an interdisciplinary subfield of computer science and artificial intelligence.It is primarily concerned with providing computers with the ability to process data encoded in natural language and is thus closely related to information retrieval, knowledge representation and computational linguistics, a subfield of linguistics.
e. Neuro-linguistic programming (NLP) is a pseudoscientific approach to communication, personal development and psychotherapy, that first appeared in Richard Bandler and John Grinder 's 1975 book The Structure of Magic I. NLP asserts that there is a connection between neurological processes, language and acquired behavioral patterns, and that ...
The methods of neuro-linguistic programming are the specific techniques used to perform and teach neuro-linguistic programming, [1] [2] which teaches that people are only able to directly perceive a small part of the world using their conscious awareness, and that this view of the world is filtered by experience, beliefs, values, assumptions, and biological sensory systems.
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The organization aims to work in the direction of human resources development, perform research and development, development of models of care and rehabilitation, prepare documentation and dissemination, offer consultancy services to voluntary organizations, conduct community-based rehabilitation and organize extension and outreach programs.
NLP USPTO: The United States Patent and Trademark Office Text NLP PhilPapers: Open access collection of philosophy publications Text NLP Book Corpus: A popular large-scale text corpus. None Text NLP 2015 [104] Zhu, Yukun, et al. Stanford Natural Language Inference (SNLI) Corpus
Representational systems (NLP) Representational systems (also abbreviated to VAKOG[1]) is a postulated model from neuro-linguistic programming, [2] a collection of models and methods regarding how the human mind processes and stores information. The central idea of this model is that experience is represented in the mind in sensorial terms, i.e ...
Timeline of natural language processing models. In 1990, the Elman network, using a recurrent neural network, encoded each word in a training set as a vector, called a word embedding, and the whole vocabulary as a vector database, allowing it to perform such tasks as sequence-predictions that are beyond the power of a simple multilayer perceptron.