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Data Mining in Streams and Graphs

This presentation by C. Faloutsos at CALD Day '06 delves into the challenges and methodologies of data mining in dynamic environments. It covers the definition and motivations behind data mining, elucidates the structure of real-world graphs, and examines the behavior of numerical streams. The talk emphasizes the relevance of power laws in graphs and introduces forecasting techniques applicable to data streams. The insights gained are pivotal for advancements in data analysis and pattern recognition in complex networks.

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Data Mining in Streams and Graphs

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