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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 ...
Natural language processing (NLP) is a subfield of computer science and especially 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.
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 ...
NLU has been considered an AI-hard problem. [ 2 ] There is considerable commercial interest in the field because of its application to automated reasoning , [ 3 ] machine translation , [ 4 ] question answering , [ 5 ] news-gathering, text categorization , voice-activation , archiving, and large-scale content analysis .
This means that the tutoring occurs in the form of an ongoing conversation, with human input presented using either voice or free text input. To handle this input, AutoTutor uses computational linguistics algorithms including latent semantic analysis, regular expression matching, and speech act classifiers. These complementary techniques focus ...
Explanation-based learning (EBL) is a form of machine learning that exploits a very strong, or even perfect, domain theory (i.e. a formal theory of an application domain akin to a domain model in ontology engineering, not to be confused with Scott's domain theory) in order to make generalizations or form concepts from training examples. [1]
Probabilistic context-free grammar (PCFG) – another name for stochastic context-free grammar. Stochastic context-free grammar (SCFG) – Systemic functional grammar (SFG) – Tree-adjoining grammar (TAG) – Natural language – n-gram – sequence of n number of tokens, where a "token" is a character, syllable, or word. The n is replaced by ...
Conceptual dependency theory is a model of natural language understanding used in artificial intelligence systems.. Roger Schank at Stanford University introduced the model in 1969, in the early days of artificial intelligence. [1]