52 packages tagged with “similarity”
A .NET port of java-string-similarity.
This class library calculates a score from 0 to 1 based on the similarity of two supplied strings.
Universal cheminformatics toolkit
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. Based upon F23.StringSimilarity
A utility library for comparing strings via the Longest Common Sequence algorithm
A utility library for comparing strings via Cosine Similarity
A utility library for comparing strings via the Jaccard similarity algorithm
A utility library for comparing strings via trie (prefix tree) similarity
A small library for computing Gower similarity coefficients in F#
Package Description
A simple dll that contains a matching class to match strings and to calculate the score of similarity between the two strings using the Ratcliff-Obershelp algorithm.
CommonPrefixes is a simple static library that evalutes a list of strings and returns a list of strings representing the common prefixes found amongst list members based on a user-specified delimiter.
Library for fuzzy string matching. Can be used to find doublets or similarities between strings. -string metrics (Levenshtein, Jaccard, JaroWinkler,...) -algorithms (SortedNeigborhood, Blocking) -phonetic codecs(Soundex, DoubleMetaphone, Phonix, ...) -string tokenizer (NGram, Whitespace, Word,..) Samples can be found in the github sources
.Net (C#) Binding for Babel Street Analytics API
Dynamic Time Warping (DTW) algorithm
This library is written for image comparison operations. Bu kütüphane resim karşılaştırma işlemleri için yazılmıştır. NOTE!!!: Because the black and white of the library is converted to color, its success in color is low. NOT!!!: Kütüphanede siyah beyaza çevirme yapıldığından renkli resimlerdeki başarısı düşüktür.
Dynamic Time Warping (DTW) algorithm visualization
Extensions to calculate the similarity between strings..
Client sdk for using Mag3llan user similarity service
Vector embedding storage for semantic search in DevGPT. Provides IEmbeddingStore interface with PostgreSQL/pgvector backend, batch operations, similarity matching, and embedding generation service. Essential for RAG implementations.
HNSWIndex provides a high-performance, approximate nearest-neighbor search solution using the HNSW data structure. It supports custom distance metrics, efficient searching with concurrency, and configurable parameters to balance speed, recall, and memory usage. Perfect for .NET applications that require fast similarity lookups (e.g., image retrieval, recommendation systems, or vector-based search).
dotnet tool to find similarities b/w 2 sets of titles (Excel sheets)
Simple and clean string metrics implementations: Hamming, Levenshtein and Damerau-Levenshtein
Uses N-Grams to categorise text and other data. Useful for processing human-written content.
BlueSimilarity is a string similarity metric library with semantic learning optimized for speed and simple usage (edit distance - Levenshtein, Damerau-Levenshtein; Levenshtein, Damerau-Levenshtein, Jaro, Jaro-Winkler, Jaccard, Dice, Overlap, Semantic Bag of Words Similarity, TFIDF, SoftTFIDF)
Activity from UiPath that can be able to look for similarity between terms in a Data Table.
A .NET port of the Apache Commons Text FuzzyScore algorithm
Embeddings support for language models, providing vector operations and similarity calculations.
Library is used to perform fuzzy matching (matching simillar strings). It uses Levenshtein Distance algorithms to perform this operation. In information theory, linguistics and computer science, the Levenshtein distance is a string metric for measuring the difference between two sequences. Informally, the Levenshtein distance between two words is the minimum number of single-character edits (insertions, deletions or substitutions) required to change one word into the other. It is named after the Soviet mathematician Vladimir Levenshtein, who considered this distance in 1965.[1] https://en.wikipedia.org/wiki/Levenshtein_distance Levenshtein distance may also be referred to as edit distance, although that term may also denote a larger family of distance metrics.[2]:32 It is closely related to pairwise string alignments.
A small evaluation tool to calculate the jaccard similarity index and distance. It also includes mean jaccard index and distance which considers the order of the elements as well.