To represent and manipulate data extracted from Web-server logs or applicational logs, clustering techniques can be used. The generated clusters are often different in types, are generated by using different algorithms, and should be homogeneously manipulated together with other knowledge mined from data, for example association rules or decision trees. The problem thus arises of using an homogeneous framework in which cluster results can be represented and manipulated, possibly together with other data mining results. In this paper, we show how the pattern modeling framework presented in [5,10] can be used to this purpose.
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