On quantitative evaluation of clustering systems
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, includ...
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Institutional Knowledge at Singapore Management University
2003
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sg-smu-ink.sis_research-62082020-07-23T18:40:55Z On quantitative evaluation of clustering systems HE, Ji TAN, Ah-hwee TAN, Chew-Lim SUNG, Sam-Yuan 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. 2003-01-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/5205 info:doi/10.1007/978-1-4613-0227-8_4 https://ink.library.smu.edu.sg/context/sis_research/article/6208/viewcontent/He02Clustering.dvi.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Cluster System Cluster Quality Adaptive Resonance Theory Pattern Representation Codebook Size Databases and Information Systems OS and Networks |
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Cluster System Cluster Quality Adaptive Resonance Theory Pattern Representation Codebook Size Databases and Information Systems OS and Networks |
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Cluster System Cluster Quality Adaptive Resonance Theory Pattern Representation Codebook Size Databases and Information Systems OS and Networks HE, Ji TAN, Ah-hwee TAN, Chew-Lim SUNG, Sam-Yuan On quantitative evaluation of clustering systems |
| description |
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. |
| format |
text |
| author |
HE, Ji TAN, Ah-hwee TAN, Chew-Lim SUNG, Sam-Yuan |
| author_facet |
HE, Ji TAN, Ah-hwee TAN, Chew-Lim SUNG, Sam-Yuan |
| author_sort |
HE, Ji |
| title |
On quantitative evaluation of clustering systems |
| title_short |
On quantitative evaluation of clustering systems |
| title_full |
On quantitative evaluation of clustering systems |
| title_fullStr |
On quantitative evaluation of clustering systems |
| title_full_unstemmed |
On quantitative evaluation of clustering systems |
| title_sort |
on quantitative evaluation of clustering systems |
| publisher |
Institutional Knowledge at Singapore Management University |
| publishDate |
2003 |
| url |
https://ink.library.smu.edu.sg/sis_research/5205 https://ink.library.smu.edu.sg/context/sis_research/article/6208/viewcontent/He02Clustering.dvi.pdf |
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