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  2. Gestalt pattern matching - Wikipedia

    en.wikipedia.org/wiki/Gestalt_Pattern_Matching

    The similarity of two strings and is determined by this formula: twice the number of matching characters divided by the total number of characters of both strings. The matching characters are defined as some longest common substring [3] plus recursively the number of matching characters in the non-matching regions on both sides of the longest common substring: [2] [4]

  3. String-searching algorithm - Wikipedia

    en.wikipedia.org/wiki/String-searching_algorithm

    A string-searching algorithm, sometimes called string-matching algorithm, is an algorithm that searches a body of text for portions that match by pattern. A basic example of string searching is when the pattern and the searched text are arrays of elements of an alphabet ( finite set ) Σ.

  4. Okapi BM25 - Wikipedia

    en.wikipedia.org/wiki/Okapi_BM25

    In information retrieval, Okapi BM25 (BM is an abbreviation of best matching) is a ranking function used by search engines to estimate the relevance of documents to a given search query. It is based on the probabilistic retrieval framework developed in the 1970s and 1980s by Stephen E. Robertson , Karen Spärck Jones , and others.

  5. String metric - Wikipedia

    en.wikipedia.org/wiki/String_metric

    In mathematics and computer science, a string metric (also known as a string similarity metric or string distance function) is a metric that measures distance ("inverse similarity") between two text strings for approximate string matching or comparison and in fuzzy string searching.

  6. Approximate string matching - Wikipedia

    en.wikipedia.org/wiki/Approximate_string_matching

    Common applications of approximate matching include spell checking. [5] With the availability of large amounts of DNA data, matching of nucleotide sequences has become an important application. [1] Approximate matching is also used in spam filtering. [5] Record linkage is a common application where records from two disparate databases are matched.

  7. Cosine similarity - Wikipedia

    en.wikipedia.org/wiki/Cosine_similarity

    For text matching, the attribute vectors A and B are usually the term frequency vectors of the documents. Cosine similarity can be seen as a method of normalizing document length during comparison. In the case of information retrieval , the cosine similarity of two documents will range from 0 → 1 {\displaystyle 0\to 1} , since the term ...

  8. Fix problems reading or receiving AOL Mail

    help.aol.com/articles/fix-problems-reading-or...

    If you're having problems reading and retrieving your AOL Mail, the following troubleshooting steps: Use AOL Basic Mail. AOL Basic Mail gives you a way to see your emails in a simpler layout.

  9. Pattern matching - Wikipedia

    en.wikipedia.org/wiki/Pattern_matching

    Here, 0 is a single value pattern. Now, whenever f is given 0 as argument the pattern matches and the function returns 1. With any other argument, the matching and thus the function fail. As the syntax supports alternative patterns in function definitions, we can continue the definition extending it to take more generic arguments: