I/o-efficient Similarity Join

Pagh Rasmus, Pham Ninh, Silvestri Francesco, Stöckel Morten. Arxiv 2015

[Paper]    
ARXIV Independent LSH

We present an I/O-efficient algorithm for computing similarity joins based on locality-sensitive hashing (LSH). In contrast to the filtering methods commonly suggested our method has provable sub-quadratic dependency on the data size. Further, in contrast to straightforward implementations of known LSH-based algorithms on external memory, our approach is able to take significant advantage of the available internal memory: Whereas the time complexity of classical algorithms includes a factor of \(N^\rho\), where \(\rho\) is a parameter of the LSH used, the I/O complexity of our algorithm merely includes a factor \((N/M)^\rho\), where \(N\) is the data size and \(M\) is the size of internal memory. Our algorithm is randomized and outputs the correct result with high probability. It is a simple, recursive, cache-oblivious procedure, and we believe that it will be useful also in other computational settings such as parallel computation.

Similar Work