Parallel Tree Projection Algorithm for Sequence Mining

Abstract

Discovery of sequential patterns is becoming increasingly useful and essential in many scientific and commercial domains. Enormous sizes of available datasets and possibly large number of mined patterns demand efficient 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 processorIBM SP show that these algorithms are capable of achieving good speedups, substantially reducing the amount of the required work to find sequential patterns in large databases.

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Document Details

Document Type
Technical Report
Publication Date
Mar 29, 2001
Accession Number
AD1020011

Entities

People

  • George Karypis
  • Nivea Garg
  • Valerie Guralnik

Organizations

  • University of Minnesota

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Buildings And Structures
  • Business Administration
  • Computations
  • Computer Science
  • Computers
  • Computing Devices
  • Contracts
  • Data Mining
  • Databases
  • Decomposition
  • Delphi Method
  • Digital Data
  • Dynamic Loads
  • Engineering
  • High Performance Computing
  • Knowledge Management
  • Military Research
  • Minnesota
  • Network Science
  • New York
  • Parallel Computing
  • Sequences
  • Sparse Matrix
  • Trees (Data Structures)
  • Workload

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Distributed Systems and Data Platform Development
  • Parallel and Distributed Computing.