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Data stream mining

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

Standard

Data stream mining. / Gaber, M.; Zaslavsky, A.; Krishnaswamy, S.

Data mining and knowledge discovery handbook. ed. / O. Maimon; L. Rokach. Springer, 2010. p. 759-787.

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

Harvard

Gaber, M, Zaslavsky, A & Krishnaswamy, S 2010, Data stream mining. in O Maimon & L Rokach (eds), Data mining and knowledge discovery handbook. Springer, pp. 759-787.

APA

Gaber, M., Zaslavsky, A., & Krishnaswamy, S. (2010). Data stream mining. In O. Maimon, & L. Rokach (Eds.), Data mining and knowledge discovery handbook (pp. 759-787). Springer.

Vancouver

Gaber M, Zaslavsky A, Krishnaswamy S. Data stream mining. In Maimon O, Rokach L, editors, Data mining and knowledge discovery handbook. Springer. 2010. p. 759-787

Author

Gaber, M. ; Zaslavsky, A. ; Krishnaswamy, S. / Data stream mining. Data mining and knowledge discovery handbook. editor / O. Maimon ; L. Rokach. Springer, 2010. pp. 759-787

Bibtex

@inbook{1cf4e3ae9bae437986400ba87ecfa128,
title = "Data stream mining",
abstract = "Data mining is concerned with the process of computationally extracting hidden knowledge structures represented in models and patterns from large data repositories. It is an interdisciplinary field of study that has its roots in databases, statistics, machine learning, and data visualization. Data mining has emerged as a direct outcome of the data explosion that resulted from the success in database and data warehousing technologies over the past two decades (Fayyad, 1997,Fayyad, 1998,Kantardzic, 2003).",
author = "M. Gaber and A. Zaslavsky and S. Krishnaswamy",
year = "2010",
language = "English",
isbn = "9780387098227",
pages = "759--787",
editor = "O. Maimon and L. Rokach",
booktitle = "Data mining and knowledge discovery handbook",
publisher = "Springer",

}

RIS

TY - CHAP

T1 - Data stream mining

AU - Gaber, M.

AU - Zaslavsky, A.

AU - Krishnaswamy, S.

PY - 2010

Y1 - 2010

N2 - Data mining is concerned with the process of computationally extracting hidden knowledge structures represented in models and patterns from large data repositories. It is an interdisciplinary field of study that has its roots in databases, statistics, machine learning, and data visualization. Data mining has emerged as a direct outcome of the data explosion that resulted from the success in database and data warehousing technologies over the past two decades (Fayyad, 1997,Fayyad, 1998,Kantardzic, 2003).

AB - Data mining is concerned with the process of computationally extracting hidden knowledge structures represented in models and patterns from large data repositories. It is an interdisciplinary field of study that has its roots in databases, statistics, machine learning, and data visualization. Data mining has emerged as a direct outcome of the data explosion that resulted from the success in database and data warehousing technologies over the past two decades (Fayyad, 1997,Fayyad, 1998,Kantardzic, 2003).

M3 - Chapter (peer-reviewed)

SN - 9780387098227

SP - 759

EP - 787

BT - Data mining and knowledge discovery handbook

A2 - Maimon, O.

A2 - Rokach, L.

PB - Springer

ER -

ID: 71370