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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.
Computational linguistics is an interdisciplinary field concerned with the computational modelling of natural language, as well as the study of appropriate computational approaches to linguistic questions.
Natural language understanding. Natural language understanding (NLU) or natural language interpretation (NLI) [1] is a subset of natural language processing in artificial intelligence that deals with machine reading comprehension. NLU has been considered an AI-hard problem. [2]
Natural-language programming (NLP) is an ontology -assisted way of programming in terms of natural-language sentences, e.g. English. [1] A structured document with Content, sections and subsections for explanations of sentences forms a NLP document, which is actually a computer program. Natural language programming is not to be mixed up with ...
spaCy (/ s p eɪ ˈ s iː / spay-SEE) is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython. [3] [4] The library is published under the MIT license and its main developers are Matthew Honnibal and Ines Montani, the founders of the software company Explosion.
Natural language generation (NLG) is a software process that produces natural language output. A widely-cited survey of NLG methods describes NLG as "the subfield of artificial intelligence and computational linguistics that is concerned with the construction of computer systems that can produce understandable texts in English or other human languages from some underlying non-linguistic ...
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.
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.