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  2. Neuro-linguistic programming - Wikipedia

    en.wikipedia.org/wiki/Neuro-linguistic_programming

    [k] While some NLP practitioners have argued that the lack of empirical support is due to insufficient research which tests NLP, [l] the consensus scientific opinion is that NLP is pseudoscience [m] [n] and that attempts to dismiss the research findings based on these arguments "[constitute]s an admission that NLP does not have an evidence base ...

  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. Automatic summarization - Wikipedia

    en.wikipedia.org/wiki/Automatic_summarization

    TextRank is a general purpose graph-based ranking algorithm for NLP. Essentially, it runs PageRank on a graph specially designed for a particular NLP task. For keyphrase extraction, it builds a graph using some set of text units as vertices. Edges are based on some measure of semantic or lexical similarity between the text unit vertices. Unlike ...

  5. 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.

  6. Syntactic parsing (computational linguistics) - Wikipedia

    en.wikipedia.org/wiki/Syntactic_parsing...

    In the past, feature-based classifiers were also common, with features chosen from part-of-speech tags, sentence position, morphological information, etc. This is an () greedy algorithm, so it does not guarantee the best possible parse or even a necessarily valid parse, but it is efficient. [21]

  7. Information extraction - Wikipedia

    en.wikipedia.org/wiki/Information_extraction

    Moreover, linguistic analysis performed for unstructured text does not exploit the HTML/XML tags and the layout formats that are available in online texts. As a result, less linguistically intensive approaches have been developed for IE on the Web using wrappers , which are sets of highly accurate rules that extract a particular page's content.

  8. Sentiment analysis - Wikipedia

    en.wikipedia.org/wiki/Sentiment_analysis

    Sentiment analysis (also known as opinion mining or emotion AI) is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information.

  9. Neural scaling law - Wikipedia

    en.wikipedia.org/wiki/Neural_scaling_law

    Performance of AI models on various benchmarks from 1998 to 2024. In machine learning, a neural scaling law is an empirical scaling law that describes how neural network performance changes as key factors are scaled up or down.