enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Earley parser - Wikipedia

    en.wikipedia.org/wiki/Earley_parser

    DECLARE ARRAY S; function INIT (words) S ← CREATE_ARRAY (LENGTH (words) + 1) for k ← from 0 to LENGTH (words) do S [k] ← EMPTY_ORDERED_SET function EARLEY_PARSE (words, grammar) INIT (words) ADD_TO_SET ((γ → • S, 0), S [0]) for k ← from 0 to LENGTH (words) do for each state in S [k] do // S[k] can expand during this loop if not FINISHED (state) then if NEXT_ELEMENT_OF (state) is a ...

  3. Methods of neuro-linguistic programming - Wikipedia

    en.wikipedia.org/wiki/Methods_of_neuro...

    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.

  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 Toolkit - Wikipedia

    en.wikipedia.org/wiki/Natural_Language_Toolkit

    The Natural Language Toolkit, or more commonly NLTK, is a suite of libraries and programs for symbolic and statistical natural language processing (NLP) for English written in the Python programming language. It supports classification, tokenization, stemming, tagging, parsing, and semantic reasoning functionalities. [4]

  6. Prompt engineering - Wikipedia

    en.wikipedia.org/wiki/Prompt_engineering

    For example, a prompt may include a few examples for a model to learn from, such as asking the model to complete "maison → house, chat → cat, chien →" (the expected response being dog), [23] an approach called few-shot learning. [24] In-context learning is an emergent ability [25] of large language models.

  7. Outline of natural language processing - Wikipedia

    en.wikipedia.org/wiki/Outline_of_natural...

    AlchemyAPI – service provider of a natural-language processing API. Google, Inc. – the Google search engine is an example of automatic summarization, utilizing keyphrase extraction. Calais (Reuters product) – provider of a natural-language processing services.

  8. Word embedding - Wikipedia

    en.wikipedia.org/wiki/Word_embedding

    In natural language processing, a word embedding is a representation of a word. The embedding is used in text analysis.Typically, the representation is a real-valued vector that encodes the meaning of the word in such a way that the words that are closer in the vector space are expected to be similar in meaning. [1]

  9. For loop - Wikipedia

    en.wikipedia.org/wiki/For_loop

    In computer science, a for-loop or for loop is a control flow statement for specifying iteration. Specifically, a for-loop functions by running a section of code repeatedly until a certain condition has been satisfied. For-loops have two parts: a header and a body. The header defines the iteration and the body is the code executed once per ...