MagicPIG: LSH Sampling for Efficient LLM Generation

Locality Sensitive Hashing in Rust with Python bindings

Locality Sensitive Hashing, fuzzy-hash， min-hash, simhash, aHash, pHash, dHash。基于 Hash值的图片相似度、文本相似度

一个基于 fasttext + faiss 的商品内容相关推荐实现，nginx+uwsgi+flask / gunicorn+uvicorn+fastapi 提供api查询接口，增加Spark实现 Ansj+Word2vec+LSH+Phoenix

ProbMinHash – A Class of Locality-Sensitive Hash Algorithms for the (Probability) Jaccard Similarity

A Query Efficient Natural Language Attack in a Black Box Setting

TreeMinHash: Fast Sketching for Weighted Jaccard Similarity Estimation

Search your object with hash

Build content-based image retrieval system using deep learning, applied some large scale similarity search technicals like Kdtree, LSH, Faiss.

Recommendation System on cryptocurrency, using data collected from users' tweets + 10-Fold Cross Validation ( Based on the cryptocoins from each user's tweets, the program runs algorithms on the data, resulting in the recommendation of other cryptocoins for each user) ( readme in greek but soon to be translated in English )

使用线程池的高并发 LSH 算法， C++ 实现

An implementation of LSH Forrest based off of the following paper (http://infolab.stanford.edu/~bawa/Pub/similarity.pdf).

A semantic search indexing system designed to efficiently retrieve top matching results from a database of 20 million documents. Given the embedding of a search query, it quickly identifies and returns the most relevant documents

A Robust Library in C# for Similarity Estimation

Implementation of algorithms for big data using python, numpy, pandas.

Lab assignments for the course ID2222-Data Mining at KTH

Repository for all assignments of the course COL761: Data Mining (Fall 2020), taught at IIT Delhi

Coursera's Natural Language Processing specialization

Scaling Up Nearest Neighbor Search : How Dataset Size and Dimensionality Affect KNN Variants