Locality sensitive hashing for big data

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This project aims to solve problems to applying locality sensitive hashing (LSH) to Big Data, namely handling new similarity functions, large data volume and better efficiency. LSH is one of the most widely adopted methods for answering similarity queries, and used widely in computer science. The project is expected to provide frontier technology to applications to combat crimes in the cybersecurity space, and lead to more intelligent and real-time analysis of Big Data.