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Association rule mining discovers interesting association or correlations among a large set of data items. Association rule mining make decision making process easier by providing the important information to the user. The most of the work done in this field is concerned with mining in an isolated form, but it is not only the case and many times more than one parties are involved in this process....
Kripke structures are important modeling formalisms to understand the behavior of reactive systems. We present an approach to automatically infer Kripke structures from time series datasets. Our algorithm bridges the continuous world of time profiles and the discrete symbols of Kripke structures by incorporating a segmentation algorithm as an intermediate step. This approach identifies, in an unsupervised...
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