incorporate data dependency in the clustering process. In this research we focus on clustering categorical sequences. The method … proposed here combines model-based and heuristic clustering. In the first step, the categorical sequences are transformed by an …, in the second step, using hierarchical clustering on the matrix of distances, the sequences can be clustered. This paper …

, keyword extraction, dimensionality reduction and clustering using the diffusion map algorithm is presented. We use publicly …

in condition monitoring. The identification of operation profiles during production is therefore important. Clustering …-and-effect relationship between the operation regimes and the wear level of components. In this study unsupervised clustering technique was …

This paper presents an assessment of the renewable energy potential in Romania using a clustering based data mining … renewable energy potential for electricity generation was mapped into representative zones using K-Means clustering algorithm …