Frequent Pattern Mining Algorithms for Data Clustering

Research output: Contribution to book/anthology/report/proceedingBook chapterResearchpeer-review

Standard

Frequent Pattern Mining Algorithms for Data Clustering. / Zimek, Arthur; Assent, Ira; Vreeken , Jilles .

Frequent Pattern Mining. ed. / Charu C. Aggarwal; Jiawei Han . Springer, 2014. p. 403-423.

Research output: Contribution to book/anthology/report/proceedingBook chapterResearchpeer-review

Harvard

Zimek, A, Assent, I & Vreeken , J 2014, Frequent Pattern Mining Algorithms for Data Clustering. in CC Aggarwal & J Han (eds), Frequent Pattern Mining. Springer, pp. 403-423. https://doi.org/10.1007/978-3-319-07821-2_16

APA

Zimek, A., Assent, I., & Vreeken , J. (2014). Frequent Pattern Mining Algorithms for Data Clustering. In C. C. Aggarwal, & J. Han (Eds.), Frequent Pattern Mining (pp. 403-423). Springer. https://doi.org/10.1007/978-3-319-07821-2_16

CBE

Zimek A, Assent I, Vreeken J. 2014. Frequent Pattern Mining Algorithms for Data Clustering. Aggarwal CC, Han J, editors. In Frequent Pattern Mining. Springer. pp. 403-423. https://doi.org/10.1007/978-3-319-07821-2_16

MLA

Zimek, Arthur, Ira Assent and Jilles Vreeken "Frequent Pattern Mining Algorithms for Data Clustering". and Aggarwal, Charu C. Han , Jiawei (editors). Frequent Pattern Mining. Springer. 2014, 403-423. https://doi.org/10.1007/978-3-319-07821-2_16

Vancouver

Zimek A, Assent I, Vreeken J. Frequent Pattern Mining Algorithms for Data Clustering. In Aggarwal CC, Han J, editors, Frequent Pattern Mining. Springer. 2014. p. 403-423 https://doi.org/10.1007/978-3-319-07821-2_16

Author

Zimek, Arthur ; Assent, Ira ; Vreeken , Jilles . / Frequent Pattern Mining Algorithms for Data Clustering. Frequent Pattern Mining. editor / Charu C. Aggarwal ; Jiawei Han . Springer, 2014. pp. 403-423

Bibtex

@inbook{a553f385afa949e8abbe2b86934cbf9c,
title = "Frequent Pattern Mining Algorithms for Data Clustering",
abstract = "Discovering clusters in subspaces, or subspace clustering and related clustering paradigms, is a research field where we find many frequent pattern mining related influences. In fact, as the first algorithms for subspace clustering were based on frequent pattern mining algorithms, it is fair to say that frequent pattern mining was at the cradle of subspace clustering—yet, it quickly developed into an independent research field.In this chapter, we discuss how frequent pattern mining algorithms have been extended and generalized towards the discovery of local clusters in high-dimensional data. In particular, we discuss several example algorithms for subspace clustering or projected clustering as well as point out recent research questions and open topics in this area relevant to researchers in either clustering or pattern mining",
keywords = "Subspace clustering, Monotonicity, Redundancy",
author = "Arthur Zimek and Ira Assent and Jilles Vreeken",
year = "2014",
doi = "10.1007/978-3-319-07821-2_16",
language = "English",
isbn = "978-3-319-07820-5",
pages = "403--423",
editor = "{ Aggarwal}, {Charu C. } and { Han }, {Jiawei }",
booktitle = "Frequent Pattern Mining",
publisher = "Springer",

}

RIS

TY - CHAP

T1 - Frequent Pattern Mining Algorithms for Data Clustering

AU - Zimek, Arthur

AU - Assent, Ira

AU - Vreeken , Jilles

PY - 2014

Y1 - 2014

N2 - Discovering clusters in subspaces, or subspace clustering and related clustering paradigms, is a research field where we find many frequent pattern mining related influences. In fact, as the first algorithms for subspace clustering were based on frequent pattern mining algorithms, it is fair to say that frequent pattern mining was at the cradle of subspace clustering—yet, it quickly developed into an independent research field.In this chapter, we discuss how frequent pattern mining algorithms have been extended and generalized towards the discovery of local clusters in high-dimensional data. In particular, we discuss several example algorithms for subspace clustering or projected clustering as well as point out recent research questions and open topics in this area relevant to researchers in either clustering or pattern mining

AB - Discovering clusters in subspaces, or subspace clustering and related clustering paradigms, is a research field where we find many frequent pattern mining related influences. In fact, as the first algorithms for subspace clustering were based on frequent pattern mining algorithms, it is fair to say that frequent pattern mining was at the cradle of subspace clustering—yet, it quickly developed into an independent research field.In this chapter, we discuss how frequent pattern mining algorithms have been extended and generalized towards the discovery of local clusters in high-dimensional data. In particular, we discuss several example algorithms for subspace clustering or projected clustering as well as point out recent research questions and open topics in this area relevant to researchers in either clustering or pattern mining

KW - Subspace clustering

KW - Monotonicity

KW - Redundancy

U2 - 10.1007/978-3-319-07821-2_16

DO - 10.1007/978-3-319-07821-2_16

M3 - Book chapter

SN - 978-3-319-07820-5

SP - 403

EP - 423

BT - Frequent Pattern Mining

A2 - Aggarwal, Charu C.

A2 - Han , Jiawei

PB - Springer

ER -