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  2. MeCab - Wikipedia

    en.wikipedia.org/wiki/MeCab

    MeCab analyzes and segments a sentence into its parts of speech. There are several dictionaries available for MeCab, but IPADIC is the most commonly used one as with ChaSen. In 2007, Google used MeCab to generate n-gram data for a large corpus of Japanese text, which it published on its Google Japan blog.

  3. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    IWE combines Word2vec with a semantic dictionary mapping technique to tackle the major challenges of information extraction from clinical texts, which include ambiguity of free text narrative style, lexical variations, use of ungrammatical and telegraphic phases, arbitrary ordering of words, and frequent appearance of abbreviations and acronyms ...

  4. DICT - Wikipedia

    en.wikipedia.org/wiki/DICT

    The standard dictd [7] server made by the DICT Development Group [1] uses a special dict file format. It comprises two files, a .index file and a .dict file (or .dict.dz if compressed). These files are usually generated by a program called dictfmt. For example, the Unix command:

  5. Wide and narrow data - Wikipedia

    en.wikipedia.org/wiki/Wide_and_narrow_data

    Many statistical and data processing systems have functions to convert between these two presentations, for instance the R programming language has several packages such as the tidyr package. The pandas package in Python implements this operation as "melt" function which converts a wide table to a narrow one. The process of converting a narrow ...

  6. Dictionary coder - Wikipedia

    en.wikipedia.org/wiki/Dictionary_coder

    A dictionary coder, also sometimes known as a substitution coder, is a class of lossless data compression algorithms which operate by searching for matches between the text to be compressed and a set of strings contained in a data structure (called the 'dictionary') maintained by the encoder. When the encoder finds such a match, it substitutes ...

  7. Sparse dictionary learning - Wikipedia

    en.wikipedia.org/wiki/Sparse_dictionary_learning

    Sparse dictionary learning (also known as sparse coding or SDL) is a representation learning method which aims to find a sparse representation of the input data in the form of a linear combination of basic elements as well as those basic elements themselves. These elements are called atoms, and they compose a dictionary.

  8. Multiple correspondence analysis - Wikipedia

    en.wikipedia.org/wiki/Multiple_correspondence...

    In the statistical analysis it is necessary to take into account this structure. This is the aim of multiple factor analysis which balances the different issues (i.e. the different groups of variables) within a global analysis and provides, beyond the classical results of factorial analysis (mainly graphics of individuals and of categories ...

  9. NumPy - Wikipedia

    en.wikipedia.org/wiki/NumPy

    NumPy (pronounced / ˈ n ʌ m p aɪ / NUM-py) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. [3]