This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
Dimensional reduction may be effective in order to compress data without loss of essential information. Also, it may be useful in order to smooth data and reduce random noise. The...
Clustering is the process of grouping a set of objects into classes of similar objects. Although definitions of similarity vary from one clustering model to another, in most of th...
Haixun Wang, Wei Wang 0010, Jiong Yang, Philip S. ...
A new genetic algorithm to detect communities in social networks is presented. The algorithm uses a fitness function able to identify groups of nodes in the network having dense ...
— In recent applications of clustering such as gene expression microarray analysis, collaborative filtering, and web mining, object similarity is no longer measured by physical ...