Search Results for "levenshtein distance"

"Natural" is a general natural language facility for nodejs. It offers a broad range of functionalities for natural language processing. Tokenizing, stemming, classification, phonetics, tf-idf, WordNet, string similarity, and some inflections are currently supported. It’s still in the early stages, so we’re very interested in bug reports, contributions and the like. Note that many algorithms from Rob Ellis’s node-nltools are being merged into this project and will be maintained from here...

Essential Excel Add-In is a Microsoft Excel Add-In, written in VBA, that contains useful User Defined Functions (UDFs) and macros to performs a number of different tasks that either Excel does not provide (Regular Expressions (RegEx), improved VLookUp).

SmartFind is an efficient file search and copy utility that uses fuzzy matching to locate files even when you don't remember the exact filenames. It calculates the similarity between filenames and search terms using the Levenshtein distance algorithm, allowing you to find files with partial or slightly varied names. With customizable search options and similarity thresholds, SmartFind gives you control over the matching process. It supports single-directory and recursive search, intelligently...

NLP.js is an NLP library for building bots, with entity extraction, sentiment analysis, automatic language identifier, and much more. "NLP.js" is a general natural language utility for nodejs. Search the best substring of a string with less Levenshtein distance to a given pattern. Get stemmers and tokenizers for several languages. Sentiment Analysis for phrases (with negation support). Named Entity Recognition and management, multi-language support, and acceptance of similar strings, so...

The goal of this project is to provide a generator for lexical analyzers of maximum computational efficiency and maximum range of applications. This includes the support for Unicode (UTF8, UTF16, ...) and a large variety of other encodings directly and via nested converters such as ICU(tm) and IConv. Sophisticated buffer handling allows to operate on plain file streams, on sockets, or manually fed buffer content. 'Ready-to-build' examples explain related concepts and facilitate practical...

Implementation of various string similarity and distance algorithms: Levenshtein, Jaro-winkler, n-Gram, Q-Gram, Jaccard index, Longest Common Subsequence edit distance, cosine similarity. A library implementing different string similarity and distance measures. A dozen of algorithms (including Levenshtein edit distance and sibblings, Jaro-Winkler, Longest Common Subsequence, cosine similarity etc.) are currently implemented. The main characteristics of each implemented algorithm are presented...

We’ve made it our mission to pull in event tickets from every corner of the internet, showing you them all on the same screen so you can compare them and get to your game/concert/show as quickly as possible. Of course, a big problem with most corners of the internet is labeling. One of our most consistently frustrating issues is trying to figure out whether two ticket listings are for the same real-life event (that is, without enlisting the help of our army of interns). To pick an example...

The fuzzy-matching library provides an OmniMark pattern function that attempts to approximately match the input prefix against any of the given target strings. The allowed Damerau–Levenshtein distance from each target string is user-specified. This distance equals the minimum number of character deletions, insertions, replacements, and transpositions required to transform the target string into the input. Each of the four transformations can be individually weighed or completely disallowed.

A Java package that provides several computations related to the edit distance of strings. Other than the basic Levenshtein, this algorithm can rearange words when comparing. The class can also provide details of how words could be transformed.

Implementation of Damerau-Levenshtein fuzzy string matching in Java. Returns the distance adding one point per character insert, deletion, mismatche and swap.. This is an extension of apache/commons/lang/StringUtils.getLevenshteinDistance()

jAlgorithms is a project mainly for educational purposes. It contains some of the popular algorithms and data structures.

Nimble dictionary is a light weighted implementation of a dictionary. It hides the details of a multi-branch tree structure of dictionary and has a very simple interface. It allows exact match as well as search within some edit (Levenshtein) distance.