approximate_string_matching
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The bitap algorithm (also known as the shift-or , shift-and or Baeza–Yates–Gonnet algorithm) is an approximate string matching algorithm. The algorithm tells whether a given text contains a substring which is "approximately equal" to a given pattern, where approximate equality is defined in terms of Levenshtein distance — if the substring and pattern are within a given distance k of each other, then the algorithm considers them equal.
Bitap algorithm - Wikipedia, the free encyclopedia
In computer science , approximate string matching (often colloquially referred to as fuzzy string searching ) is the technique of finding strings that match a pattern approximately (rather than exactly). The problem of approximate string matching is typically divided into two sub-problems: finding approximate substring matches inside a given string and finding dictionary strings that match the pattern approximately. [ edit ] Overview
Approximate string matching - Wikipedia, the free encyclopedia
Hamming distance - Wikipedia, the free encyclopedia
Two example distances: 0100->1001 has distance 3 (red path); 0110->1110 has distance 1 (blue path)
Dice's coefficient , named after Lee Raymond Dice [ 1 ] and also known as the Dice coefficient , is a similarity measure over sets:
Dice's coefficient - Wikipedia, the free encyclopedia
This page exists because the original home page seems to have disappeared.
pylevenshtein - A fast implementation of Levenshtein Distance (and others) for Python - Google Project Hosting
SimString - A fast and simple algorithm for approximate string matching/retrieval
A fast and simple algorithm for approximate string matching/retrieval
7.4. difflib — Helpers for computing deltas — Python v2.7.2 documentation
New in version 2.1. This module provides classes and functions for comparing sequences. It can be used for example, for comparing files, and can produce difference information in various formats, including HTML and context and unified diffs.
