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  2. Text mining - Wikipedia

    en.wikipedia.org/wiki/Text_mining

    Text mining. Text mining, text data mining (TDM) or text analytics is the process of deriving high-quality information from text. It involves "the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources." [1] Written resources may include websites, books, emails ...

  3. Word embedding - Wikipedia

    en.wikipedia.org/wiki/Word_embedding

    e. In natural language processing (NLP), 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]

  4. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    e. Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words. The word2vec algorithm estimates these representations by modeling text in a large corpus. Once trained, such a model can detect synonymous ...

  5. Mining - Wikipedia

    en.wikipedia.org/wiki/Mining

    Mining. Mining of sulfur from a deposit at the edge of Ijen 's crater lake, Indonesia. Mining is the extraction of valuable geological materials and minerals from the surface of the Earth. Mining is required to obtain most materials that cannot be grown through agricultural processes, or feasibly created artificially in a laboratory or factory.

  6. Stemming - Wikipedia

    en.wikipedia.org/wiki/Stemming

    Stemming. In linguistic morphology and information retrieval, stemming is the process of reducing inflected (or sometimes derived) words to their word stem, base or root form—generally a written word form. The stem need not be identical to the morphological root of the word; it is usually sufficient that related words map to the same stem ...

  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 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). It disregards word order (and thus most of syntax or grammar) but captures multiplicity. The bag-of-words model is commonly ...

  8. Topic model - Wikipedia

    en.wikipedia.org/wiki/Topic_model

    Topic model. In statistics and natural language processing, a topic model is a type of statistical model for discovering the abstract "topics" that occur in a collection of documents. Topic modeling is a frequently used text-mining tool for discovery of hidden semantic structures in a text body. Intuitively, given that a document is about a ...

  9. Text corpus - Wikipedia

    en.wikipedia.org/wiki/Text_corpus

    Text corpus. In linguistics and natural language processing, a corpus (pl.: corpora) or text corpus is a dataset, consisting of natively digital and older, digitalized, language resources, either annotated or unannotated. Annotated, they have been used in corpus linguistics for statistical hypothesis testing, checking occurrences or validating ...