PURG
发表于 2025-3-23 11:21:17
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Hippocampus
发表于 2025-3-23 17:06:06
Animesh Adhikari,Pralhad Ramachandrarao,Witold PedOne of the first books on multi-database data mining..Discusses the various issues regarding the systematic and efficient development of multi-database mining applications.
Intrepid
发表于 2025-3-23 18:33:13
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成份
发表于 2025-3-24 01:58:16
https://doi.org/10.1007/978-3-531-92533-2that possess multiple databases. Global decisions made by such an organization might be more appropriate if they are based on the data distributed over the branches. Moreover, the number of such applications is increasing over time. In this chapter, we discuss some of the major challenges encountere
就职
发表于 2025-3-24 04:21:59
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小画像
发表于 2025-3-24 08:11:41
https://doi.org/10.1007/978-3-662-66456-8y from multiple databases, it becomes necessary to improve mining multiple databases. In this chapter, we present an idea of multi-database mining by making use of local pattern analysis. We elaborate on the existing specialized and generalized techniques which are used for mining multiple large dat
熄灭
发表于 2025-3-24 12:13:57
https://doi.org/10.1007/978-3-662-66456-8es becomes of primordial relevance. In this chapter, we focus on the following issues. First, a model of mining global patterns of select items from multiple databases is presented. Second, a measure of quantifying an overall association between two items in a database is discussed. Third, we presen
慷慨不好
发表于 2025-3-24 17:13:25
Glücksangebote in der Alltagsweltt of view, it might be required to enhance the quality of knowledge synthesized from multiple databases. Also, many decision-making applications are directly based on the available local patterns present in different databases. The quality of synthesized knowledge/decision based on local patterns pr
乐器演奏者
发表于 2025-3-24 20:26:18
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违反
发表于 2025-3-25 01:20:02
https://doi.org/10.1007/978-3-322-83250-4cuss how one can systematically prepare data warehouses located at different branches for ensuring data mining activities. An appropriate multi-database mining technique is essential to develop efficient applications. Also, the efficiency of a multi-database mining application could be improved by p