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The significant growth of interconnected Internet‐of‐Things (IoT) devices, the use of social networks, along with the evolution of technology in different domains, lead to a rise in the volume of data generated continuously from multiple systems. Valuable information can be derived from these evolving data streams by applying machine learning. In practice, several critical issues emerge when extracting...
Clustering is a crucial task for massive data that continuously arrive and evolve over time, generated as stream. However, data may be pervaded by uncertainty and imprecision, and techniques that achieve the unsupervised learning with imperfect data sets are unable to deal with such evolving environment. On the other hand, standard methods for clustering data streams are not adapted to an uncertain...
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