Parallel Tree Projection Algorithm for Sequence Mining

Discovery of sequential patterns is becoming increasingly useful and essential in many scienti c and commercial domains. Enormous sizes of available datasets and possibly large number of mined patterns demand e cient and scalable algorithms. In this paper we present two parallel formulations of a serial sequential pattern discovery algorithm based on tree projection that are well suited for distributed memory parallel computers. Our experimental evaluation on a 32 processor IBM SP show that these algorithms are capable of achieving good speedups, substantially reducing the amount of the required work to nd sequential patterns in large databases.