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
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;
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
DOI :
10.1109/NAFIPS.2010.5548181