Density based subspace clustering over dynamic data

Hans Peter Kriegel*, Peer Kröger, Irene Ntoutsi, Arthur Zimek

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Modern data are often high dimensional and dynamic. Subspace clustering aims at finding the clusters and the dimensions of the high dimensional feature space where these clusters exist. So far, the subspace clustering methods are mainly static and cannot address the dynamic nature of modern data. In this paper, we propose a dynamic subspace clustering method, which extends the density based projected clustering algorithm PreDeCon for dynamic data. The proposed method efficiently examines only those clusters that might be affected due to the population update. Both single and batch updates are considered.

Original languageEnglish
Title of host publicationScientific and Statistical Database Management - 23rd International Conference, SSDBM 2011, Proceedings
EditorsD. Pfoser
PublisherSpringer
Publication date11. Aug 2011
Pages387-404
ISBN (Print)978-3-642-22921-3
ISBN (Electronic)978-3-642-22922-0
DOIs
Publication statusPublished - 11. Aug 2011
Externally publishedYes
Event23rd International Conference on Scientific and Statistical Database Management - Portland, United States
Duration: 20. Jul 201122. Jul 2011

Conference

Conference23rd International Conference on Scientific and Statistical Database Management
CountryUnited States
CityPortland
Period20/07/201122/07/2011
SponsorMicrosoft Research, University of Washington, The Gordon and Betty Moore Foundation, Paradigm4 Inc.
SeriesLecture Notes in Computer Science
Volume6849
ISSN0302-9743

Fingerprint

Clustering algorithms

Cite this

Kriegel, H. P., Kröger, P., Ntoutsi, I., & Zimek, A. (2011). Density based subspace clustering over dynamic data. In D. Pfoser (Ed.), Scientific and Statistical Database Management - 23rd International Conference, SSDBM 2011, Proceedings (pp. 387-404). Springer. Lecture Notes in Computer Science, Vol.. 6849 https://doi.org/10.1007/978-3-642-22351-8_24
Kriegel, Hans Peter ; Kröger, Peer ; Ntoutsi, Irene ; Zimek, Arthur. / Density based subspace clustering over dynamic data. Scientific and Statistical Database Management - 23rd International Conference, SSDBM 2011, Proceedings. editor / D. Pfoser. Springer, 2011. pp. 387-404 (Lecture Notes in Computer Science, Vol. 6849).
@inproceedings{df3fbbb6b8c84a099d7b0d15ad7420b0,
title = "Density based subspace clustering over dynamic data",
abstract = "Modern data are often high dimensional and dynamic. Subspace clustering aims at finding the clusters and the dimensions of the high dimensional feature space where these clusters exist. So far, the subspace clustering methods are mainly static and cannot address the dynamic nature of modern data. In this paper, we propose a dynamic subspace clustering method, which extends the density based projected clustering algorithm PreDeCon for dynamic data. The proposed method efficiently examines only those clusters that might be affected due to the population update. Both single and batch updates are considered.",
author = "Kriegel, {Hans Peter} and Peer Kr{\"o}ger and Irene Ntoutsi and Arthur Zimek",
year = "2011",
month = "8",
day = "11",
doi = "10.1007/978-3-642-22351-8_24",
language = "English",
isbn = "978-3-642-22921-3",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "387--404",
editor = "D. Pfoser",
booktitle = "Scientific and Statistical Database Management - 23rd International Conference, SSDBM 2011, Proceedings",
address = "Germany",

}

Kriegel, HP, Kröger, P, Ntoutsi, I & Zimek, A 2011, Density based subspace clustering over dynamic data. in D Pfoser (ed.), Scientific and Statistical Database Management - 23rd International Conference, SSDBM 2011, Proceedings. Springer, Lecture Notes in Computer Science, vol. 6849, pp. 387-404, 23rd International Conference on Scientific and Statistical Database Management, Portland, United States, 20/07/2011. https://doi.org/10.1007/978-3-642-22351-8_24

Density based subspace clustering over dynamic data. / Kriegel, Hans Peter; Kröger, Peer; Ntoutsi, Irene; Zimek, Arthur.

Scientific and Statistical Database Management - 23rd International Conference, SSDBM 2011, Proceedings. ed. / D. Pfoser. Springer, 2011. p. 387-404 (Lecture Notes in Computer Science, Vol. 6849).

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

TY - GEN

T1 - Density based subspace clustering over dynamic data

AU - Kriegel, Hans Peter

AU - Kröger, Peer

AU - Ntoutsi, Irene

AU - Zimek, Arthur

PY - 2011/8/11

Y1 - 2011/8/11

N2 - Modern data are often high dimensional and dynamic. Subspace clustering aims at finding the clusters and the dimensions of the high dimensional feature space where these clusters exist. So far, the subspace clustering methods are mainly static and cannot address the dynamic nature of modern data. In this paper, we propose a dynamic subspace clustering method, which extends the density based projected clustering algorithm PreDeCon for dynamic data. The proposed method efficiently examines only those clusters that might be affected due to the population update. Both single and batch updates are considered.

AB - Modern data are often high dimensional and dynamic. Subspace clustering aims at finding the clusters and the dimensions of the high dimensional feature space where these clusters exist. So far, the subspace clustering methods are mainly static and cannot address the dynamic nature of modern data. In this paper, we propose a dynamic subspace clustering method, which extends the density based projected clustering algorithm PreDeCon for dynamic data. The proposed method efficiently examines only those clusters that might be affected due to the population update. Both single and batch updates are considered.

U2 - 10.1007/978-3-642-22351-8_24

DO - 10.1007/978-3-642-22351-8_24

M3 - Article in proceedings

AN - SCOPUS:79961204635

SN - 978-3-642-22921-3

T3 - Lecture Notes in Computer Science

SP - 387

EP - 404

BT - Scientific and Statistical Database Management - 23rd International Conference, SSDBM 2011, Proceedings

A2 - Pfoser, D.

PB - Springer

ER -

Kriegel HP, Kröger P, Ntoutsi I, Zimek A. Density based subspace clustering over dynamic data. In Pfoser D, editor, Scientific and Statistical Database Management - 23rd International Conference, SSDBM 2011, Proceedings. Springer. 2011. p. 387-404. (Lecture Notes in Computer Science, Vol. 6849). https://doi.org/10.1007/978-3-642-22351-8_24