A new distributed data mining model based on similarity

Tao Li, Shenghuo Zhu, Mitsunori Ogihara

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

21 Citations (Scopus)

Abstract

Distributed Data Mining(DDM) has been very active and enjoying a growing amount attention since its inception. Current DDM techniques regard the distributed data sets as a single virtual table and assume there exists a global model which could be generated if the data were combined/centralized. This paper proposes a similarity-based distributed data mining(SBDDM) framework which explicitly take the differences among distributed sources into consideration. A new similarity measure is introduced and its effectiveness is then evaluated and validated. This paper also illustrates the limitations of current DDM techniques through three concrete case studies. Finally distributed clustering within the SBDDM framework is also discussed.

Original languageEnglish (US)
Title of host publicationProceedings of the ACM Symposium on Applied Computing
EditorsG. Lamont
Pages432-436
Number of pages5
StatePublished - 2003
Externally publishedYes
EventProceedings of the 2003 ACM Symposium on Applied Computing - Melbourne, FL, United States
Duration: Mar 9 2003Mar 12 2003

Other

OtherProceedings of the 2003 ACM Symposium on Applied Computing
CountryUnited States
CityMelbourne, FL
Period3/9/033/12/03

Fingerprint

Data mining

Keywords

  • Distributed Data Mining(DDM)
  • SBDDM
  • Similarity

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Li, T., Zhu, S., & Ogihara, M. (2003). A new distributed data mining model based on similarity. In G. Lamont (Ed.), Proceedings of the ACM Symposium on Applied Computing (pp. 432-436)

A new distributed data mining model based on similarity. / Li, Tao; Zhu, Shenghuo; Ogihara, Mitsunori.

Proceedings of the ACM Symposium on Applied Computing. ed. / G. Lamont. 2003. p. 432-436.

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

Li, T, Zhu, S & Ogihara, M 2003, A new distributed data mining model based on similarity. in G Lamont (ed.), Proceedings of the ACM Symposium on Applied Computing. pp. 432-436, Proceedings of the 2003 ACM Symposium on Applied Computing, Melbourne, FL, United States, 3/9/03.
Li T, Zhu S, Ogihara M. A new distributed data mining model based on similarity. In Lamont G, editor, Proceedings of the ACM Symposium on Applied Computing. 2003. p. 432-436
Li, Tao ; Zhu, Shenghuo ; Ogihara, Mitsunori. / A new distributed data mining model based on similarity. Proceedings of the ACM Symposium on Applied Computing. editor / G. Lamont. 2003. pp. 432-436
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