I/O-Efficient Similarity Join

Rasmus Pagh, Ninh Dang Pham, Francesco Silvestri, Morten Stöckel

Publikation: Konference artikel i Proceeding eller bog/rapport kapitelKonferencebidrag i proceedingsForskningpeer review


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 ρ, where ρ is a parameter of the LSH used, the I/O complexity
of our algorithm merely includes a factor (N/M)ρ, 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.
TitelAlgorithms - ESA 2015 : 23rd Annual European Symposium, Patras, Greece, September 14-16, 2015, Proceedings
Antal sider12
Publikationsdato14 sep. 2015
ISBN (Trykt)978-3-662-48349-7
ISBN (Elektronisk)978-3-662-48350-3
StatusUdgivet - 14 sep. 2015
NavnLecture Notes in Computer Science


Dyk ned i forskningsemnerne om 'I/O-Efficient Similarity Join'. Sammen danner de et unikt fingeraftryk.