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  2. Approximate string matching - Wikipedia

    en.wikipedia.org/wiki/Approximate_string_matching

    The closeness of a match is measured in terms of the number of primitive operations necessary to convert the string into an exact match. This number is called the edit distance between the string and the pattern. The usual primitive operations are: [1] insertion: cot → coat; deletion: coat → cot; substitution: coat → cost

  3. Comparison of programming languages (string functions)

    en.wikipedia.org/wiki/Comparison_of_programming...

    rfind(string,substring) returns integer Description Returns the position of the start of the last occurrence of substring in string. If the substring is not found most of these routines return an invalid index value – -1 where indexes are 0-based, 0 where they are 1-based – or some value to be interpreted as Boolean FALSE. Related instr

  4. Access Database Engine - Wikipedia

    en.wikipedia.org/wiki/Access_Database_Engine

    Jet, being part of a relational database management system (RDBMS), allows the manipulation of relational databases. [1] It offers a single interface that other software can use to access Microsoft databases and provides support for security, referential integrity, transaction processing, indexing, record and page locking, and data replication.

  5. Longest common substring - Wikipedia

    en.wikipedia.org/wiki/Longest_common_substring

    The picture shows two strings where the problem has multiple solutions. Although the substring occurrences always overlap, it is impossible to obtain a longer common substring by "uniting" them. The strings "ABABC", "BABCA" and "ABCBA" have only one longest common substring, viz. "ABC" of length 3.

  6. 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]

  7. 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.

  8. Rabin–Karp algorithm - Wikipedia

    en.wikipedia.org/wiki/Rabin–Karp_algorithm

    The hash function described here is not a Rabin fingerprint, but it works equally well. It treats every substring as a number in some base, the base being usually the size of the character set. For example, if the substring is "hi", the base is 256, and prime modulus is 101, then the hash value would be

  9. Knuth–Morris–Pratt algorithm - Wikipedia

    en.wikipedia.org/wiki/Knuth–Morris–Pratt...

    In computer science, the Knuth–Morris–Pratt algorithm (or KMP algorithm) is a string-searching algorithm that searches for occurrences of a "word" W within a main "text string" S by employing the observation that when a mismatch occurs, the word itself embodies sufficient information to determine where the next match could begin, thus bypassing re-examination of previously matched characters.