Cluster Algorithm for Time Series Based on Key Points
Yong Zhang · 2012
Based on key point technology,a new method for time series cluster was proposed.The key points for each time series were first found,and then the complex network was constructed by calculating the similarity between key point series after they were equidimensional.At last,the clustering time series were implemented by partitioning the complex network into communities.The experimental results show that the dimensions of time series and the consumption of computing time can be effectively reduced by the proposal.Furthermore,the desired cluster result is obtained when applying this method to cluster some practical data.