Publication Type
Book Chapter
Version
acceptedVersion
Publication Date
1-2003
Abstract
Clustering refers to the task of partitioning unlabelled data into meaningful groups (clusters). It is a useful approach in data mining processes for identifying hidden patterns and revealing underlying knowledge from large data collections. The application areas of clustering, to name a few, include image segmentation, information retrieval, document classification, associate rule mining, web usage tracking, and transaction analysis.
Keywords
Cluster System, Cluster Quality, Adaptive Resonance Theory, Pattern Representation, Codebook Size
Discipline
Databases and Information Systems | OS and Networks
Research Areas
Data Science and Engineering
Publication
Clustering and Information Retrieval
Volume
11
Editor
WU, Weili; XONG, Hui; SHASHI, Shekhar
First Page
105
Last Page
133
ISBN
9781461379492
Identifier
10.1007/978-1-4613-0227-8_4
Publisher
Springer
Citation
HE, Ji; TAN, Ah-hwee; TAN, Chew-Lim; and SUNG, Sam-Yuan.
On quantitative evaluation of clustering systems. (2003). Clustering and Information Retrieval. 11, 105-133.
Available at: https://ink.library.smu.edu.sg/sis_research/5205
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1007/978-1-4613-0227-8_4