There are 0 repository under levenshtein-algorithm topic.
A Levenshtein Distance implementation using C++ with a dynamic programming approach.
VBA Functions/Subs for performing fuzzy matching in Excel Workbooks.
Less-wrong single-file Numba-accelerated Python implementation of Gotoh affine gap penalty extensions for the Needleman–Wunsch, Smith-Waterman, and Levenshtein algorithms for sequence alignment
Efficient typo-tolerant search in 76 lines of code, with no dependencies.
Shortens the paragraph depending on the given keywords using Levenshtein distance
Created modified Levenshtein distance algorithms, to match strings by deletion and capitalization only and does not allow replacement or insertion of characters
Web-based text aligner and comparator
Implementation of Levenshtein Algorithm
Bot Dialog Flow Telegram untuk memenuhi Tugas Akhir Matakuliah Multi Channel Access
Calculates similarity between two Korean strings using Levenshtein distance with decomposed phonemes, improving accuracy.
:robot: ChatBot program, which is able to discuss some C++ related topics based on the content of a knowledge base.
[VUE] - Visual dynamic algorithm using levenshtein and KMP search algorithm.
This C++ and C# repository holds a variety of common pattern-matching algorithms
Implemented various spellcheck techniques like cosine similarity, jaccard similarity and levenshtein distance. Open to any further contributions.
C++/Assembler language program simulating the operation of autocorrect using the Levenshtein (Editing Distance) Algorithm. [PL]
Implementation of the Levenshtein Algorithm in x86 Assembler (for multi-threaded use). [ENG]
A fuzzy match library exposed by rest endpoint written in GoLang
The Levenshtein distance algorithm calculates the minimum number of operations required to transform one string into another. The operations can be insertion, deletion, or substitution of a single character. The higher the Levenshtein distance between two strings, the more different they are.
Here Is Program To Check The Spelling And Correction in Spelling mistake suggester
Python scripts used to calculate 3 basic similarity measures, suitable for ad hoc information retrieval systems: Levenshtein Edit Distance, Jaccard, and a Term-Document matrix.
Fuzzy search using Levenshtein Distance (LD) and Longest Common Substring (LCS) algorithm.
Simple package to implement levenshtein distance algorithm in typescript
Find the best match for a token word with dictionary via min edit distance and levenshtein
This sample compare two text files similarity using memory efficient Levenshtein algorithm.
Finding matching concepts in OCL MSF Source