TNTSearch is a full-text search (FTS) engine written entirely in PHP. A simple configuration allows you to add an amazing search experience in just minutes. Its features include Fuzzy search, Geo-search, Text classification, Stemming, Bm25 ranking algorithm, Result highlighting, Boolean search and lot more.
fulltext search search-engine full-text-search fuzzy-search geo-search fuzzy fuzzy-matching tntsearch laravel-scoutThis plugin is mainly used for locating files, buffers, mrus, tags in large project. To install this plugin just put the plugin files in your ~/.vim (Linux) or ~/vimfiles (Windows). For Vundle user, just add Plugin 'Yggdroot/LeaderF' to your .vimrc.
fuzzy-search fuzzy-matching fuzzyfinder mru ctags vim fuzzySpelling 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.
levenshtein fuzzy-search approximate-string-matching edit-distance spellcheck spell-check levenshtein-distance damerau-levenshtein spelling fuzzy-matching word-segmentation chinese-text-segmentation chinese-word-segmentation text-segmentation spelling-correction symspellFuse is a super lightweight library which provides a simple way to do fuzzy searching. To run the example project, clone the repo, and run pod install from the Example directory first.
weighted-search bitap fuzzy-search fuzzy-matchingThe library's full documentation can be found here. Be sure to lint & pass the unit tests before submitting your pull request.
natural-language-processing machine-learning fuzzy-matching clustering record-linkage bayes bloom-filter canberra caverphone chebyshev cologne cosine classifier daitch-mokotoff dice fingerprint fuzzy hamming k-means jaccard jaro lancaster levenshtein lig metaphone mra ngrams nlp nysiis perceptron phonetic porter punkt schinke sorensen soundex stats tfidf tokenizer tversky vectorizer winklerZingg is a scalable fuzzy matching for data mastering, deduplication and entity resolution. Real world data contains multiple records belonging to the same customer. These records can be in single or multiple systems and they have variations across fields which makes it hard to combine them together, especially with growing data volumes. Zingg integrates different records of an entity like customer, patient, supplier, product etc in same or disparate data sources.
data-science identity-resolution spark etl dedupe entity-resolution data-transformation ml fuzzy-matching deduplication masterdata dataengineering fuzzymatch dataquality datapreparation analytics-engineering data-transformationsFlex matching short abbreviations against longer strings is a boon in productivity for typists. Applications like Quicksilver, Alfred, LaunchBar, and Launchy have made this method of keyboard entry a popular one. It's time to bring this same functionality to web controls. LiquidMetal makes scoring long strings against abbreviations easy.If you like this project, buy me a coffee, donate via Gratipay, or book a session with me on Codementor.
fuzzy-matching fuzzy-searchclosestmatch 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).
levenshtein fuzzy-matching string-matching golang-libraryVladimir Levenshtein’s edit distance algorithm1 as a C library. There’s also a CLI: levenshtein(1), and a JavaScript version.Or clone the repo.
levenshtein fuzzy-search edit-distance fuzzy-matching string-matching similarity levenshtein-distance vladimir algorithm edit distanceCopy the autocomplete-ALL-the-things file to the urxvt perl-lib directory (default: ~/.urxvt/ext/). Completes the currently typed word using the other words visible in the urxvt window.
urxvt autocomplete fuzzy-matchingBased directly on the percol plugin. fzy picks up history item and adds it to your shell. You need to execute manually.
fish-shell fish-plugin fzy fuzzy-search fuzzy-matchingrefinr is designed to cluster and merge similar values within a character vector. It features two functions that are implementations of clustering algorithms from the open source software OpenRefine. The cluster methods used are key collision and ngram fingerprint (more info on these here). In addition, there are a few add-on features included, to make the clustering/merging functions more useful. These include approximate string matching to allow for merging despite minor mispellings, the option to pass a dictionary vector to dictate edit values, and the option to pass a vector of strings to ignore during the clustering process.
openrefine fuzzy-matching ngram approximate-string-matching data-cleaning data-clustering clustering cran r rstatsvim-picker is a fuzzy picker for Neovim and Vim. To use vim-picker you will first need a fuzzy selector such as fzy (recommended), pick, or selecta installed. See their respective homepages for installation instructions.
neovim vim vim-plugin fuzzy-matching fuzzy-search fzy pick selecta
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