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  2. LCP array - Wikipedia

    en.wikipedia.org/wiki/LCP_array

    In order to find the number of occurrences of a given string (length ) in a text (length ), [3] We use binary search against the suffix array of T {\displaystyle T} to find the starting and end position of all occurrences of P {\displaystyle P} .

  3. FM-index - Wikipedia

    en.wikipedia.org/wiki/FM-index

    In computer science, an FM-index is a compressed full-text substring index based on the Burrows–Wheeler transform, with some similarities to the suffix array.It was created by Paolo Ferragina and Giovanni Manzini, [1] who describe it as an opportunistic data structure as it allows compression of the input text while still permitting fast substring queries.

  4. 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.

  5. Template:Str count - Wikipedia

    en.wikipedia.org/wiki/Template:Str_count

    There are three parameters; the first two are required: |source= – the source string.Required; alias: |1=. |pattern= – the search-string or pattern to look for in the source string.

  6. Frequency (statistics) - Wikipedia

    en.wikipedia.org/wiki/Frequency_(statistics)

    A frequency distribution shows a summarized grouping of data divided into mutually exclusive classes and the number of occurrences in a class. It is a way of showing unorganized data notably to show results of an election, income of people for a certain region, sales of a product within a certain period, student loan amounts of graduates, etc.

  7. Run-length encoding - Wikipedia

    en.wikipedia.org/wiki/Run-length_encoding

    Run-length encoding (RLE) is a form of lossless data compression in which runs of data (consecutive occurrences of the same data value) are stored as a single occurrence of that data value and a count of its consecutive occurrences, rather than as the original run. As an imaginary example of the concept, when encoding an image built up from ...

  8. String-searching algorithm - Wikipedia

    en.wikipedia.org/wiki/String-searching_algorithm

    A simple and inefficient way to see where one string occurs inside another is to check at each index, one by one. First, we see if there is a copy of the needle starting at the first character of the haystack; if not, we look to see if there's a copy of the needle starting at the second character of the haystack, and so forth.

  9. Index of dispersion - Wikipedia

    en.wikipedia.org/wiki/Index_of_dispersion

    The relevance of the index of dispersion is that it has a value of 1 when the probability distribution of the number of occurrences in an interval is a Poisson distribution. Thus the measure can be used to assess whether observed data can be modeled using a Poisson process. When the coefficient of dispersion is less than 1, a dataset is said to ...