DocumentCode
3530436
Title
A new approach to improve the accuracy of online clustering algorithm based on scatter/gather model
Author
Farsandaj, Kian ; Ding, Chen ; Sadeghian, Alireza
Author_Institution
Dept. of Comput. Sci., Ryerson Univ., Toronto, ON, Canada
fYear
2010
fDate
12-14 July 2010
Firstpage
1
Lastpage
5
Abstract
In cluster analysis process used in data mining which enables extracting interesting data patterns from datasets, accuracy and efficiency are the factors which play a pivotal role. Scatter/Gather is a cluster-based browsing model, and most of previous works on this model focused on efficiency of the clustering algorithm. In this paper we present an algorithm which could improve the accuracy of the online clustering algorithm while still maintain a reasonable level of efficiency. Our experiment proves that the new algorithm is more accurate than the original algorithm.
Keywords
data mining; pattern clustering; cluster analysis process; cluster based browsing model; data mining; online clustering algorithm; scatter-gather model; Algorithm design and analysis; Clustering algorithms; Clustering methods; Computer science; Couplings; Data mining; Partitioning algorithms; Pattern analysis; Prototypes; Scattering; Accuracy; Algorithms; Clustering; Data Mining; Efficiency; Homogeneity; Performance; Rand Index; Scatter/Gather;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Information Processing Society (NAFIPS), 2010 Annual Meeting of the North American
Conference_Location
Toronto, ON
Print_ISBN
978-1-4244-7859-0
Electronic_ISBN
978-1-4244-7857-6
Type
conf
DOI
10.1109/NAFIPS.2010.5548181
Filename
5548181
Link To Document