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  2. Natural language processing - Wikipedia

    en.wikipedia.org/wiki/Natural_language_processing

    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.

  3. Bag-of-words model - Wikipedia

    en.wikipedia.org/wiki/Bag-of-words_model

    The bag-of-words model (BoW) is a model of text which uses a representation of text that is based on an unordered collection (a "bag") of words.It is used in natural language processing and information retrieval (IR).

  4. Natural-language programming - Wikipedia

    en.wikipedia.org/wiki/Natural-language_programming

    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 ...

  5. Natural language generation - Wikipedia

    en.wikipedia.org/wiki/Natural_language_generation

    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 ...

  6. Natural language understanding - Wikipedia

    en.wikipedia.org/wiki/Natural_language_understanding

    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.

  7. Explanation-based learning - Wikipedia

    en.wikipedia.org/wiki/Explanation-Based_Learning

    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]

  8. Artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Artificial_intelligence

    Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. [1]

  9. Prompt engineering - Wikipedia

    en.wikipedia.org/wiki/Prompt_engineering

    Prompt engineering is the process of structuring an instruction that can be interpreted and understood by a generative artificial intelligence (AI) model. [ 1 ] [ 2 ] A prompt is natural language text describing the task that an AI should perform. [ 3 ]