When.com Web Search

  1. Ads

    related to: nltk remove punctuation and stopwords key generator free

Search results

  1. Results From The WOW.Com Content Network
  2. Stop word - Wikipedia

    en.wikipedia.org/wiki/Stop_word

    In this case, stop words can cause problems when searching for phrases that include them, particularly in names such as "The Who", "The The", or "Take That". Other search engines remove some of the most common words—including lexical words , such as "want"—from a query in order to improve performance.

  3. Sentence boundary disambiguation - Wikipedia

    en.wikipedia.org/wiki/Sentence_boundary...

    Things such as shortened names, e.g. "D. H. Lawrence" (with whitespaces between the individual words that form the full name), idiosyncratic orthographical spellings used for stylistic purposes (often referring to a single concept, e.g. an entertainment product title like ".hack//SIGN") and usage of non-standard punctuation (or non-standard ...

  4. Natural Language Toolkit - Wikipedia

    en.wikipedia.org/wiki/Natural_Language_Toolkit

    Parse tree generated with NLTK. 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 ...

  5. Comparison of parser generators - Wikipedia

    en.wikipedia.org/.../Comparison_of_parser_generators

    However, parser generators for context-free grammars often support the ability for user-written code to introduce limited amounts of context-sensitivity. (For example, upon encountering a variable declaration, user-written code could save the name and type of the variable into an external data structure, so that these could be checked against ...

  6. Lexical analysis - Wikipedia

    en.wikipedia.org/wiki/Lexical_analysis

    For a simple quoted string literal, the evaluator needs to remove only the quotes, but the evaluator for an escaped string literal incorporates a lexer, which unescapes the escape sequences. For example, in the source code of a computer program, the string net_worth_future = (assets – liabilities);

  7. 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 an unordered collection (a "bag") of words.It is used in natural language processing and information retrieval (IR).

  8. spaCy - Wikipedia

    en.wikipedia.org/wiki/SpaCy

    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.

  9. Stemming - Wikipedia

    en.wikipedia.org/wiki/Stemming

    NLTK – Software suite for natural language processing — implements several stemming algorithms in Python Root (linguistics) – Core of a word that is irreducible into more meaningful elements Snowball (programming language) – String processing programming language — designed for creating stemming algorithms