Summarizing Cluster Evolution in Dynamic Environments

, , and . Computational Science and Its Applications - ICCSA 2011, volume 6783 of Lecture Notes in Computer Science, Springer Berlin Heidelberg, (2011)
DOI: 10.1007/978-3-642-21887-3_43


Monitoring and interpretation of changing patterns is a task of paramount importance for data mining applications in dynamic environments. While there is much research in adapting patterns in the presence of drift or shift, there is less research on how to maintain an overview of pattern changes over time. A major challenge lays in summarizing changes in an effective way, so that the nature of change can be understood by the user, while the demand on resources remains low. To this end, we propose FINGERPRINT, an environment for the summarization of cluster evolution. Cluster changes are captured into an “evolution graph”, which is then summarized based on cluster similarity into a

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