Document Type
Conference Item
Publication Date
7-1-2011
Abstract
There are considerable advances in clustering time series data in data mining concept. However, most of which use traditional approaches and try to customize the algorithms to be compatible with time series data. One of the significant problems with traditional clustering is defining prototype specially in partitional clustering where it needs centroids as representative of each cluster. In this paper we present a novel effective approach to define the prototypes based on time series nature. The prototype is constructed based on fuzzy concept efficiently. Moreover, it is demonstrated how the prototypes are moved in iterations. We will present the benefits of the proposed prototype by implementing a real application: Customer transactions clustering.
Event Title
Proceedings of The 2011 International Conference on Data Mining
Event Location
Las Vegas, USA
Event Dates
18-21 July 2011
Event Type
conference