lsh-implementation
There are 16 repositories under lsh-implementation topic.
guofei9987/pyLSHash
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
EastTower16/LLMDataDistill
distill large scale web page text
munnafaisal/Deep-Object-Search-With-Hash
Search your object with hash
theatina/CryptoRecommendation
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 )
RikilG/Locality-Sensitive-Hashing
An implementation of Locality sensitive hashing
ronald-smith-angel/dataset_deduplication_sparkml
Dataset deduplication using the spark ML lib and Scala
GiorgioMorales/CSCI550-ImageRetrieval
Image Retrieval implementation using Deep Learning and Kernelized Locality-Sensitive Hashing
shaltielshmid/MinHashSharp
A Robust Library in C# for Similarity Estimation
spChalk/kNN-and-Clustering-on-Curves-and-Time-Series
:chart_with_upwards_trend: kNN using LSH and Hypercube projection & Clustering using kMeans++ for n-dim polygonal curves and time series
AGiannoutsos/Latent_vs_Original_Space_Image_Classification
Image classification and unsupervised learning using latent space vectors produced by convolutional neural nets together with the original vectors space
IbraheemTaha/Song_Similarity_ForestLSH
This is a task using python to find number of similar songs within the provided songs set.
Sitaras/Software-Development-for-Algorithmic-Problems_Project-1
Vectors - Nearest neighbor search and Clustering using LSH, Hypercube (and Lloyd's only at the clustering) algorithms with L2 metric.
XAH30/LSH-vs-Finesse
In this repository you can find an implementation of LSH (Local | Sensitive Hashing) and Finesse algorithms, designed to find similar data based on their hashes
Joseph0472/AlgorithmsforMD
Implementation tasks for multiple algorithms to process massive data. The algorithms are written in Python.
Sitaras/Software-Development-for-Algorithmic-Problems_Project-2
📈|Time Series - Nearest neighbor search and Clustering using LSH, Hypercube (and Lloyd's only at the clustering) algorithms with metrics: L2, Discrete and Continuous Fréchet.
pedroalbanese/lshsum
TTAK.KO-12.0276 LSH Recursive Hasher