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Titlebook: Data Mining for Business Applications; Longbing Cao,Philip S. Yu,Huaifeng Zhang Book 2009 Springer-Verlag US 2009 Business Decision Making

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樓主: adulation
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發(fā)表于 2025-3-23 10:10:57 | 只看該作者
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發(fā)表于 2025-3-23 14:26:05 | 只看該作者
https://doi.org/10.1057/9781137002693ion systems and target marketing systems in e-business. However, pattern-based clustering in large databases is still challenging. On the one hand, there can be a huge number of clusters and many of them can be redundant and thus make the pattern-based clustering ineffective. On the other hand, the
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發(fā)表于 2025-3-23 18:58:14 | 只看該作者
https://doi.org/10.1007/978-1-349-03354-6eparation, modeling, evaluation and deployment. Various data mining tasks are dependent on the human user for their execution. These tasks and activities that require human intelligence are not amenable to automation like tasks in other phases such as data preparation or modeling are. Nearly all Dat
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發(fā)表于 2025-3-24 00:14:14 | 只看該作者
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發(fā)表于 2025-3-24 04:43:30 | 只看該作者
https://doi.org/10.1007/978-1-349-03354-6a Mining methodologies acknowledge the importance of the human user but do not clearly delineate and explain the tasks where human intelligence should be leveraged or in what manner. In this chapter we propose to describe various tasks of the domain understanding phase which require human intelligence for their appropriate execution.
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發(fā)表于 2025-3-24 09:26:06 | 只看該作者
ssues in data mining, including trust, organizational and so.Data Mining for Business Applications. presents the state-of-the-art research and development outcomes on methodologies, techniques, approaches and successful applications in the area. The contributions mark a paradigm shift from “data-cen
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發(fā)表于 2025-3-24 12:35:16 | 只看該作者
Book 2009uccessful applications in the area. The contributions mark a paradigm shift from “data-centered pattern mining” to “domain driven actionable knowledge discovery” for next-generation KDD research and applications. The contents identify how KDD techniques can better contribute to critical domain probl
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發(fā)表于 2025-3-24 16:25:43 | 只看該作者
Role of Human Intelligence in Domain Driven Data Mininga Mining methodologies acknowledge the importance of the human user but do not clearly delineate and explain the tasks where human intelligence should be leveraged or in what manner. In this chapter we propose to describe various tasks of the domain understanding phase which require human intelligence for their appropriate execution.
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發(fā)表于 2025-3-24 21:39:37 | 只看該作者
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發(fā)表于 2025-3-25 01:42:33 | 只看該作者
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