NDLI: Density-Based Data Streams Clustering over Sliding Windows

Content Provider	IEEE Xplore Digital Library
Author	Jiadong Ren Ruiqing Ma
Copyright Year	2009
Abstract	Data stream clustering is an important task in data stream mining. In this paper, we propose SDStream, a new method for performing density-based data streams clustering over sliding windows. SDStream adopts CluStream clustering framework. In the online component, the potential core-micro-cluster and outlier micro-cluster structures are introduced to maintain the potential clusters and outliers. They are stored in the form of Exponential Histogram of Cluster Feature (EHCF) in main memory and are maintained by the maintenance of EHCFs. Outdated micro-clusters which need to be deleted are found by the value of t in Temporal Cluster Feature (TCF). In the offline component, the final clusters of arbitrary shape are generated according to all the potential core-micro-clusters maintained online by DBSCAN algorithm. Experimental results show that SDStream which can generate clusters of arbitrary shape has a much higher clustering quality than CluStream which generates spherical clusters.
Starting Page	248
Ending Page	252
File Size	356614
Page Count	5
File Format	PDF
ISBN	9780769537351
DOI	10.1109/FSKD.2009.553
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Shape density-based clustering Data structures Educational institutions Partitioning algorithms Electronic mail Data mining sliding windows data stream Histograms Clustering algorithms Cities and towns Fuzzy systems
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Density-Based Data Streams Subspace Clustering over Weighted Sliding Windows

A fast subspace partition clustering algorithm for high dimensional data streams

Mineral cities competitiveness based on fuzzy clustering algorithm

Research and application of fuzzy-clustering algorithm based on pretreatment of similarity relation

A density-based clustering over evolving heterogeneous data stream

Clustering Algorithm for High Dimensional Data Stream over Sliding Windows

Mining Frequent Patterns in Data Stream over Sliding Windows

A Multi Density-Based Clustering Algorithm for Data Stream with Noise

A Frequent Itemsets Mining Algorithm Based on Matrix in Sliding Window over Data Streams

Density-Based Data Streams Clustering over Sliding Windows

Similar Documents

Density-Based Data Streams Subspace Clustering over Weighted Sliding Windows

A fast subspace partition clustering algorithm for high dimensional data streams

Mineral cities competitiveness based on fuzzy clustering algorithm

Research and application of fuzzy-clustering algorithm based on pretreatment of similarity relation

A density-based clustering over evolving heterogeneous data stream

Clustering Algorithm for High Dimensional Data Stream over Sliding Windows

Mining Frequent Patterns in Data Stream over Sliding Windows

A Multi Density-Based Clustering Algorithm for Data Stream with Noise

A Frequent Itemsets Mining Algorithm Based on Matrix in Sliding Window over Data Streams

Density-Based Data Streams Clustering over Sliding Windows