An Efficient Algorithm for Dense Regions Discovery from Large-Scale Data Streams

Andy M. Yip; Edmond H. Wu; Michael K. Ng; Tony F. Chan

doi:10.1007/978-3-540-24775-3_14

An Efficient Algorithm for Dense Regions Discovery from Large-Scale Data Streams

Andy M. Yip, Edmond H. Wu, Michael K. Ng, Tony F. Chan

Department of Mathematics

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

4 Citations (Scopus)

Abstract

We introduce the notion of dense region as distinct and meaningful patterns from given data. Efficient and effective algorithms for identifying such regions are presented. Next, we discuss extensions of the algorithms for handling data streams. Finally, experiments on largescale data streams such as clickstreams are given which confirm that the usefulness of our algorithms.

Original language	English
Title of host publication	Advances in Knowledge Discovery and Data Mining
Subtitle of host publication	8th Pacific-Asia Conference, PAKDD 2004, Sydney, Australia, May 26-28, 2004, Proceedings
Editors	Honghua Dai, Ramakrishnan Srikant, Chengqi Zhang
Publisher	Springer Berlin Heidelberg
Pages	116-120
Number of pages	5
Edition	1st
ISBN (Electronic)	9783540247753
ISBN (Print)	354022064X, 9783540220640
DOIs	https://doi.org/10.1007/978-3-540-24775-3_14
Publication status	Published - 22 Apr 2004
Event	8th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2004 - Sydney, Australia Duration: 26 May 2004 → 28 May 2004 https://link.springer.com/book/10.1007/b97861 (Conference proceedings)

Publication series

Name	Lecture Notes in Computer Science
Volume	3056
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Name	Lecture Notes in Artificial Intelligence
ISSN (Print)	2945-9133
ISSN (Electronic)	2945-9141

Name	PAKDD: Pacific-Asia Conference on Knowledge Discovery and Data Mining

Conference

Conference	8th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2004
Abbreviated title	PAKDD 2004
Country/Territory	Australia
City	Sydney
Period	26/05/04 → 28/05/04
Internet address	https://link.springer.com/book/10.1007/b97861 (Conference proceedings)

Scopus Subject Areas

Theoretical Computer Science
General Computer Science

User-Defined Keywords

Bayesian network
algorithms
classification
data mining
knowledge discovery
multimedia
service-oriented computing
web mining

Access to Document

10.1007/978-3-540-24775-3_14

Cite this

Yip, A. M., Wu, E. H., Ng, M. K., & Chan, T. F. (2004). An Efficient Algorithm for Dense Regions Discovery from Large-Scale Data Streams. In H. Dai, R. Srikant, & C. Zhang (Eds.), Advances in Knowledge Discovery and Data Mining: 8th Pacific-Asia Conference, PAKDD 2004, Sydney, Australia, May 26-28, 2004, Proceedings (1st ed., pp. 116-120). (Lecture Notes in Computer Science; Vol. 3056), (Lecture Notes in Artificial Intelligence), (PAKDD: Pacific-Asia Conference on Knowledge Discovery and Data Mining). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-24775-3_14

Yip, Andy M. ; Wu, Edmond H. ; Ng, Michael K. et al. / An Efficient Algorithm for Dense Regions Discovery from Large-Scale Data Streams. Advances in Knowledge Discovery and Data Mining: 8th Pacific-Asia Conference, PAKDD 2004, Sydney, Australia, May 26-28, 2004, Proceedings. editor / Honghua Dai ; Ramakrishnan Srikant ; Chengqi Zhang. 1st. ed. Springer Berlin Heidelberg, 2004. pp. 116-120 (Lecture Notes in Computer Science). (Lecture Notes in Artificial Intelligence). (PAKDD: Pacific-Asia Conference on Knowledge Discovery and Data Mining).

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title = "An Efficient Algorithm for Dense Regions Discovery from Large-Scale Data Streams",

abstract = "We introduce the notion of dense region as distinct and meaningful patterns from given data. Efficient and effective algorithms for identifying such regions are presented. Next, we discuss extensions of the algorithms for handling data streams. Finally, experiments on largescale data streams such as clickstreams are given which confirm that the usefulness of our algorithms.",

keywords = "Bayesian network, algorithms, classification, data mining, knowledge discovery, multimedia, service-oriented computing, web mining",

author = "Yip, {Andy M.} and Wu, {Edmond H.} and Ng, {Michael K.} and Chan, {Tony F.}",

note = "Funding Information: The research of this author is partially supported by grants from NSF under contracts DMS-9973341 and ACI-0072112, ONR under contract N00014-02-1-0015 and NIH under contract P20 MH65166. The research of this author is supported in part by Hong Kong Research Grants Council Grant Nos. HKU 7130/02P and HKU 7046/03P. Publisher Copyright: {\textcopyright} 2004 Springer-Verlag Berlin Heidelberg; 8th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2004, PAKDD 2004 ; Conference date: 26-05-2004 Through 28-05-2004",

year = "2004",

month = apr,

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doi = "10.1007/978-3-540-24775-3_14",

language = "English",

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series = "Lecture Notes in Computer Science",

publisher = "Springer Berlin Heidelberg",

pages = "116--120",

editor = "Honghua Dai and Ramakrishnan Srikant and Chengqi Zhang",

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Yip, AM, Wu, EH, Ng, MK & Chan, TF 2004, An Efficient Algorithm for Dense Regions Discovery from Large-Scale Data Streams. in H Dai, R Srikant & C Zhang (eds), Advances in Knowledge Discovery and Data Mining: 8th Pacific-Asia Conference, PAKDD 2004, Sydney, Australia, May 26-28, 2004, Proceedings. 1st edn, Lecture Notes in Computer Science, vol. 3056, Lecture Notes in Artificial Intelligence, PAKDD: Pacific-Asia Conference on Knowledge Discovery and Data Mining, Springer Berlin Heidelberg, pp. 116-120, 8th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2004, Sydney, Australia, 26/05/04. https://doi.org/10.1007/978-3-540-24775-3_14

An Efficient Algorithm for Dense Regions Discovery from Large-Scale Data Streams. / Yip, Andy M.; Wu, Edmond H.; Ng, Michael K. et al.
Advances in Knowledge Discovery and Data Mining: 8th Pacific-Asia Conference, PAKDD 2004, Sydney, Australia, May 26-28, 2004, Proceedings. ed. / Honghua Dai; Ramakrishnan Srikant; Chengqi Zhang. 1st. ed. Springer Berlin Heidelberg, 2004. p. 116-120 (Lecture Notes in Computer Science; Vol. 3056), (Lecture Notes in Artificial Intelligence), (PAKDD: Pacific-Asia Conference on Knowledge Discovery and Data Mining).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

TY - GEN

T1 - An Efficient Algorithm for Dense Regions Discovery from Large-Scale Data Streams

AU - Yip, Andy M.

AU - Wu, Edmond H.

AU - Ng, Michael K.

AU - Chan, Tony F.

N1 - Funding Information: The research of this author is partially supported by grants from NSF under contracts DMS-9973341 and ACI-0072112, ONR under contract N00014-02-1-0015 and NIH under contract P20 MH65166. The research of this author is supported in part by Hong Kong Research Grants Council Grant Nos. HKU 7130/02P and HKU 7046/03P. Publisher Copyright: © 2004 Springer-Verlag Berlin Heidelberg

PY - 2004/4/22

Y1 - 2004/4/22

N2 - We introduce the notion of dense region as distinct and meaningful patterns from given data. Efficient and effective algorithms for identifying such regions are presented. Next, we discuss extensions of the algorithms for handling data streams. Finally, experiments on largescale data streams such as clickstreams are given which confirm that the usefulness of our algorithms.

AB - We introduce the notion of dense region as distinct and meaningful patterns from given data. Efficient and effective algorithms for identifying such regions are presented. Next, we discuss extensions of the algorithms for handling data streams. Finally, experiments on largescale data streams such as clickstreams are given which confirm that the usefulness of our algorithms.

KW - Bayesian network

KW - algorithms

KW - classification

KW - data mining

KW - knowledge discovery

KW - multimedia

KW - service-oriented computing

KW - web mining

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SN - 354022064X

SN - 9783540220640

T3 - Lecture Notes in Computer Science

SP - 116

EP - 120

BT - Advances in Knowledge Discovery and Data Mining

A2 - Dai, Honghua

A2 - Srikant, Ramakrishnan

A2 - Zhang, Chengqi

PB - Springer Berlin Heidelberg

T2 - 8th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2004

Y2 - 26 May 2004 through 28 May 2004

ER -

Yip AM, Wu EH, Ng MK, Chan TF. An Efficient Algorithm for Dense Regions Discovery from Large-Scale Data Streams. In Dai H, Srikant R, Zhang C, editors, Advances in Knowledge Discovery and Data Mining: 8th Pacific-Asia Conference, PAKDD 2004, Sydney, Australia, May 26-28, 2004, Proceedings. 1st ed. Springer Berlin Heidelberg. 2004. p. 116-120. (Lecture Notes in Computer Science). (Lecture Notes in Artificial Intelligence). (PAKDD: Pacific-Asia Conference on Knowledge Discovery and Data Mining). doi: 10.1007/978-3-540-24775-3_14

An Efficient Algorithm for Dense Regions Discovery from Large-Scale Data Streams

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