Xindong Wu Livres

The book addresses the pressing challenge of efficiently mining distributed data across multiple databases, particularly in the context of the overwhelming information available on the Web. It introduces local pattern analysis, a novel approach designed to uncover valuable patterns that traditional methods may overlook. The authors discuss advancements in multi-database mining, including hierarchical meta-learning and database classification, making it a vital resource for researchers and students in data mining and machine learning, as well as a useful supplement for related courses.

This book constitutes the refereed proceedings of the Second Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD-98, held in Melbourne, Australia, in April 1998. The book presents 30 revised full papers selected from a total of 110 submissions; also included are 20 poster presentations. The papers contribute new results to all current aspects in knowledge discovery and data mining on the research level as well as on the level of systems development. Among the areas covered are machine learning, information systems, the Internet, statistics, knowledge acquisition, data visualization, software reengineering, and knowledge based systems.