Generic pattern mining via data mining template library

Mohammed J. Zaki, Nilanjana De, Feng Gao, Paolo Palmerini, Nagender Parimi, Jeevan Pathuri, Benjarath Phoophakdee, Joe Urban

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Frequent Pattern Mining (FPM) is a very powerful paradigm for mining informative and useful patterns in massive, complex datasets. In this paper we propose the Data Mining Template Library, a collection of generic containers and algorithms for data mining, as well as persistency and database management classes. DMTL provides a systematic solution to a whole class of common FPM tasks like itemset, sequence, tree and graph mining. DMTL is extensible, scalable, and high-performance for rapid response on massive datasets. A detailed set of experiments show that DMTL is competitive with special purpose algorithms designed for a particular pattern type, especially as database sizes increase.

Original languageEnglish
Title of host publicationConstraint-Based Mining and Inductive Databases - European Workshop on Inductive Databases and Constraint Based Mining, Revised Selected Papers
Pages362-379
Number of pages18
DOIs
Publication statusPublished - 23 Jun 2006
EventEuropean Workshop on Inductive Databases and Constraint Based Mining - Hinterzarten, Germany
Duration: 11 Mar 200413 Mar 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3848 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherEuropean Workshop on Inductive Databases and Constraint Based Mining
CountryGermany
CityHinterzarten
Period11/3/0413/3/04

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'Generic pattern mining via data mining template library'. Together they form a unique fingerprint.

  • Cite this

    Zaki, M. J., De, N., Gao, F., Palmerini, P., Parimi, N., Pathuri, J., Phoophakdee, B., & Urban, J. (2006). Generic pattern mining via data mining template library. In Constraint-Based Mining and Inductive Databases - European Workshop on Inductive Databases and Constraint Based Mining, Revised Selected Papers (pp. 362-379). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3848 LNAI). https://doi.org/10.1007/11615576_17