Parallel and distributed data mining: An introduction

Mohammed J. Zaki

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

13 Citations (Scopus)

Abstract

The explosive growth in data collection in business and scientific fields has literally forced upon us the need to analyze and mine useful knowledge from it. Data mining refers to the entire process of extracting useful and novel patterns/models from large datasets. Due to the huge size of data and amount of computation involved in data mining, high-performance computing is an essential component for any successful large-scale data mining application. This chapter presents a survey on large-scale parallel and distributed data mining algorithms and systems, serving as an introduction to the rest of this volume. It also discusses the issues and challenges that must be overcome for designing and implementing successful tools for large-scale data mining.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages1-23
Number of pages23
Volume1759
ISBN (Print)3540671943, 9783540671947
Publication statusPublished - 2002
Externally publishedYes
Event5th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1999 - San Diego, United States
Duration: 15 Aug 199915 Aug 1999

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1759
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other5th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1999
CountryUnited States
CitySan Diego
Period15/8/9915/8/99

Fingerprint

Distributed Data Mining
Data mining
Data Mining
Essential Component
Large Data Sets
High Performance
Entire
Computing
Industry

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Zaki, M. J. (2002). Parallel and distributed data mining: An introduction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1759, pp. 1-23). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1759). Springer Verlag.

Parallel and distributed data mining : An introduction. / Zaki, Mohammed J.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 1759 Springer Verlag, 2002. p. 1-23 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1759).

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

Zaki, MJ 2002, Parallel and distributed data mining: An introduction. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 1759, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1759, Springer Verlag, pp. 1-23, 5th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1999, San Diego, United States, 15/8/99.
Zaki MJ. Parallel and distributed data mining: An introduction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 1759. Springer Verlag. 2002. p. 1-23. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Zaki, Mohammed J. / Parallel and distributed data mining : An introduction. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 1759 Springer Verlag, 2002. pp. 1-23 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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