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

VBA Functions/Subs for performing fuzzy matching in Excel Workbooks.

A Levenshtein Distance implementation using C++ with a dynamic programming approach.

Efficient typo-tolerant search in 76 lines of code, with no dependencies.

Shortens the paragraph depending on the given keywords using Levenshtein distance

Bot Dialog Flow Telegram untuk memenuhi Tugas Akhir Matakuliah Multi Channel Access

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

Calculates similarity between two Korean strings using Levenshtein distance with decomposed phonemes, improving accuracy.

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.

[VUE] - Visual dynamic algorithm using levenshtein and KMP search algorithm.

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.

Implemented various spellcheck techniques like cosine similarity, jaccard similarity and levenshtein distance. Open to any further contributions.

This C++ and C# repository holds a variety of common pattern-matching algorithms

Finding matching concepts in OCL MSF Source

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.

🤖 ChatBot program, which is able to discuss some C++ related topics based on the content of a knowledge base.