Accelerated Clustering Through Locality - Sensitive Hashing by Shaunak Kishore

Accelerated similarity searching and clustering of large compound sets by geometric embedding and locality sensitive hashing

MOTIVATION Similarity searching and clustering of chemical compounds by structural similarities are important computational approaches for identifying drug-like small molecules. Most algorithms available for these tasks are limited by their speed and scalability, and cannot handle today's large compound databases with several million entries. RESULTS In this article, we introduce a new algori...

Kernelized Locality-Sensitive Hashing for Semi-Supervised Agglomerative Clustering

Large scale agglomerative clustering is hindered by computational burdens. We propose a novel scheme where exact inter-instance distance calculation is replaced by the Hamming distance between Kernelized Locality-Sensitive Hashing (KLSH) hashed values. This results in a method that drastically decreases computation time. Additionally, we take advantage of certain labeled data points via distanc...

Locality Sensitive K-means Clustering

Hierarchical clustering of large text datasets using Locality-Sensitive Hashing

In this paper, we present a hierarchical clustering algorithm of the large text datasets using Locality-Sensitive Hashing (LSH). The main idea of the LSH is to “hash” items several times, in such a way that similar items are more likely to be hashed to the same bucket than dissimilar are. The main drawback of the conventional hierarchical algorithms is a large time complexity (e.g. Single Linka...

High-Throughput, Web-Scale Data Stream Clustering

Clustering is an important technique for analysing and interpreting massive quantities of data present on the web. However the sheer volume of data, along with its often dynamic and fast changing nature provide a challenge for traditional clustering approaches. We present a parallel clustering system specifically designed for continuous, real-time clustering of web-scale message data streams. A...