normalized-compression-distance

Implementation of A New Burrows Wheeler Transform Markov Distance

text similarity search trees based on Normalized Compression Distance

Autonomous Agent Normalized Compression Distance (NCD) & Kolmogorov Complexity Universal Metric

Autonomous Agent Normalized Compression Distance (NCD) & Kolmogorov Complexity Universal Metric

A small Julia library for calculating the normalized compression distance.

FastNCD is a simple C++ library to calculates the Normalized Compression Distance (NCD) between two given strings

Normalized Compression Distance in POSIX shell, and compatible with any compressor.

Measure HTML structural similarity via Normalized Compression Distance

FacialSimilarity: a compression-based face identifier through image similarity.

A new package that uses large language models and pattern matching to perform structured similarity comparisons between textual content based on normalized compression distance. Users provide multiple

🔍 Analyze text similarity effortlessly with Compario, a Python package that uses advanced models to compare structured content and deliver accurate results.

Predict search relevance given a product name and its text attributes

EEG signal analysis and classification using preprocessing, segmentation and Normalized Compression Distance.

Rust version of the Burrows Wheeler Markov Distance https://github.com/EdwardRaff/pyBWMD

TAI Third Assignment - The objective is to use the Normalized Compression Distance (NCD), with multiple compressors, in order to obtain the similarity between a small music sample and every complete music in the dataset. The sample will then be assigned to the one which has the smaller average distance for all the compressors.