NDLI: Heuristic based approach to clustering and its time critical applications

Content Provider	IEEE Xplore Digital Library
Author	Chen, A.C.-L. Shang Gao Alhajj, R. Karampelas, P.
Copyright Year	2010
Description	Author affiliation: Dept of Computer Science, University of Calgary, Alberta, Canada (Chen, A.C.-L.; Shang Gao; Alhajj, R.) \|\| Dept of Information Technology, Hellenic American University, Athens, Greece (Karampelas, P.)
Abstract	Clustering may be named as the first clustering technique addressed by the research community since 1960s. However, as databases continue to grow in size, numerous research studies have been undertaken to develop more efficient clustering algorithms and to improve the performance of existing ones. This paper demonstrates a general optimization technique applicable to clustering algorithms with a need to calculate distances and check them against some minimum distance condition. The optimization technique is a simple calculation that finds the minimum possible distance between two points, and checks this distance against the minimum distance condition; thus reusing already computed values and reducing the need to compute a more complicated distance function periodically. The proposed optimization technique has been applied to the agglomerative hierarchical clustering, k-means clustering, and DBSCAN algorithms with successful results. Runtimes for all three algorithms with this optimization scenario were reduced, and the clusters they returned were verified to remain the same as the original algorithms. The optimization technique also shows potential for reducing runtimes by a substantial amount for large databases. As well, the optimization technique shows potential for reducing runtimes more and more as databases grow larger and larger.
Starting Page	37
Ending Page	42
File Size	395209
Page Count	6
File Format	PDF
ISBN	9781424480975
e-ISBN	9781424480999
DOI	10.1109/IRI.2010.5558969
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Clustering algorithms Algorithm design and analysis Optimization Runtime Databases Symmetric matrices Performance evaluation performance clustering algorithms DBSCAN density-based clustering distance computation hierarchical clustering k-means clustering
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