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)

Music recommender using deep learning with Keras and TensorFlow

Score documents using embedding-vectors dot-product or cosine-similarity with ES Lucene engine

A .NET port of java-string-similarity

Python package to accelerate the sparse matrix multiplication and top-n similarity selection

Generating multiple choice questions from text using Machine Learning.

SAX-VSM public release, visit our website for detail

Tika-Similarity uses the Tika-Python package (Python port of Apache Tika) to compute file similarity based on Metadata features.

Taking a pretrained GloVe model, and using it as a TensorFlow embedding weight layer **inside the GPU**. Therefore, you only need to send the index of the words through the GPU data transfer bus, reducing data transfer overhead.

Information Retrieval algorithms developed in python. To follow the blog posts, click on the link:

A fuzzy matching string distance library for Scala and Java that includes Levenshtein distance, Jaro distance, Jaro-Winkler distance, Dice coefficient, N-Gram similarity, Cosine similarity, Jaccard similarity, Longest common subsequence, Hamming distance, and more..

Implementation of TextRank with the option of using pre-trained Word2Vec embeddings as the similarity metric

It is a content based recommender system that uses tf-idf and cosine similarity for N Most SImilar Items from a dataset

Web Application for checking the similarity between query and document using the concept of Cosine Similarity.

Code for the blog post Nearest Neighbors with Keras and CoreML

📖 Use Bi-normal Separation to find document vectors which is used to compute similarity for shorter sentences.

There are Python 2.7 codes and learning notes for Spark 2.1.1

Food recommendation tool with Machine learning.

Vector Plugin for Solr: calculate dot product / cosine similarity on documents

計算關鍵詞重要程度(TF-IDF實作)Calculate cosine-similarity between documents using TF-IDF

Extract a feature vector for any image and find the cosine similarity for comparison using Pytorch. I have used ResNet-18 to extract the feature vector of images. Finally a Django app is developed to input two images and to find the cosine similarity.

BERT semantic search engine for searching literature research papers for coronavirus covid-19 in google colab

Locality Sensitive Hashing in Rust with Python bindings

Building Event Extraction and Trending Framework for Twitter

Deep Learning tools to explore visual storytelling. 📖 Read sample stories! 📖

Recommend movies to users by RBMs, TruncatedSVD, Stochastic SVD and Variational Inference

Train emoji embeddings based on emoji descriptions.

CS 582 Information Retrieval at University of Illinois at Chicago. Multithreaded crawling of UIC domain, inverted index, page rank, SEO with Context Pseudo-Relevance Feedback

this repo include paper review, code in face recognition