Implementation of various string similarity and distance algorithms: Levenshtein, Jaro-winkler, n-Gram, Q-Gram, Jaccard index, Longest Common Subsequence edit distance, cosine similarity ...
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Updated
Jun 1, 2022 - Java
Implementation of various string similarity and distance algorithms: Levenshtein, Jaro-winkler, n-Gram, Q-Gram, Jaccard index, Longest Common Subsequence edit distance, cosine similarity ...
FAst Lookups of Cosine and Other Nearest Neighbors (based on fast locality-sensitive hashing)
Information Retrieval algorithms developed in python. To follow the blog posts, click on the link:
Music recommender using deep learning with Keras and TensorFlow
A python project for checking plagiarism of documents based on cosine similarity
Generating multiple choice questions from text using Machine Learning.
Score documents using embedding-vectors dot-product or cosine-similarity with ES Lucene engine
TensorFlow Similarity is a python package focused on making similarity learning quick and easy.
It is a content based recommender system that uses tf-idf and cosine similarity for N Most SImilar Items from a dataset
Python package to accelerate the sparse matrix multiplication and top-n similarity selection
A .NET port of java-string-similarity
Web Application for checking the similarity between query and document using the concept of Cosine Similarity.
📈This repo contains detailed notes and multiple projects implemented in Python related to AI and Finance. Follow the blog here: https://purvasingh.medium.com
Tika-Similarity uses the Tika-Python package (Python port of Apache Tika) to compute file similarity based on Metadata features.
Spark library for generalized K-Means clustering. Supports general Bregman divergences. Suitable for clustering probabilistic data, time series data, high dimensional data, and very large data.
Blazing fast framework for fine-tuning similarity learning models
SAX-VSM public release, visit our website for detail
Vector Storage is a vector database that enables semantic similarity searches on text documents in the browser's local storage. It uses OpenAI embeddings to convert documents into vectors and allows searching for similar documents based on cosine similarity.
Designed for recruiters, Our AI-powered platform can filter out top resumes of the stack
Vector Plugin for Solr: calculate dot product / cosine similarity on documents
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