Titlebook: Knowledge Discovery in Multiple Databases; Shichao Zhang,Chengqi Zhang,Xindong Wu Book 2004 Springer-Verlag London 2004 Association rule.D

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Importance of Multi-database Mining, differences between mono- and multi-database mining. An existing process of multi-database mining is included in this chapter, and some practical issues involving mining multi-databases, including application-independent database classification, local pattern analysis, and local pattern synthesis, are briefly discussed.

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Synthesizing Local Patterns by Weighting,ay be of different importance to their company. Also, local patterns may have different supports within a branch. To take these factors into account, this chapter presents a model for synthesizing global patterns from local patterns by weighting. This model synthesizes association rules with respect to all dimensions: ., ., ., and ..

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Advanced Information and Knowledge Processinghttp://image.papertrans.cn/k/image/543879.jpg

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Database Clustering,In the past, identifying relevant databases has been typically . The process had to be carried out multiple times to identify relevant databases for two or more real-world applications. This chapter advocates an efficient and effective application-independent database classification for mining multi-databases.

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Identifying Exceptional Patterns,Techniques for identifying high-vote patterns have been developed in Chapter 7. Another new kind of pattern is the exceptional pattern which reflects the individuality of, say, branches of an interstate company. Exceptional patterns are also of interest to company headquarters in their decision-making.

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