We have collection of more than 1 Million open source products ranging from Enterprise product to
small libraries in all platforms. We aggregate information from all open source repositories.
Search and find the best for your needs. Check out projects section.
Spelling correction & Fuzzy search: 1 million times faster through Symmetric Delete spelling correction algorithm
The Symmetric Delete spelling correction algorithm reduces the complexity of edit candidate generation and dictionary lookup for a given Damerau-Levenshtein distance. It is six orders of magnitude faster (than the standard approach with deletes + transposes + replaces + inserts) and language independent.
Ogama allows recording and analyzing eye- and mouse-tracking data from slideshow eyetracking experiments in parallel. It´s developed in C#.NET and provides attention maps, AOIS, saliency, replay, levensthein distances and many more visualization tools.
closestmatch is a simple and fast Go library for fuzzy matching an input string to a list of target strings. closestmatch is useful for handling input from a user where the input (which could be mispelled or out of order) needs to match a key in a database. closestmatch uses a bag-of-words approach to precompute character n-grams to represent each possible target string. The closest matches have highest overlap between the sets of n-grams. The precomputation scales well and is much faster and more accurate than Levenshtein for long strings.closestmatch is more accurate than Levenshtein for long strings (like in the test corpus).
The library is fully capable of working with non-ascii strings. But the strings are not normalized. That is left as a user-dependant use case. Please normalize the strings before passing it to the library if you have such a requirement.Words selected are - "levenshtein" and "frankenstein".
This project implements the Approximate String Matching algorithm by Esko Ukkonen extended with ideas from An Extension of Ukkonen's Enhanced Dynamic Programming ASM Algorith by Hal Berghel and David Roach. Ukkonen's algorithm is very competitive with the Levenshtein distance and for longer strings it is much more performant than Levenshtein distance.
Apply the Levenshtein distance to transform / morph an Array into another, performing the least amount of needed .splice(...) operations. It is also possible to intercept all splice calls using an aura, which augments the splice method of the list, delegating the interceptor one.