Knowledge Discovery in Multiple Databases

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The book addresses the urgent need for efficient mining of distributed data across multiple databases, particularly in the context of the overwhelming information available on the Web. It introduces local pattern analysis, a novel strategy for uncovering valuable patterns that traditional techniques may overlook. The authors explore advancements in areas such as hierarchical meta-learning and database classification, all within the local pattern analysis framework. Aimed at researchers and students in data mining and machine learning, it serves as a valuable resource for broader courses on knowledge discovery.