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Data Mining for Business Applications.pdf
(10.62 MB, 需要: 4 个论坛币)
首先声明，论坛上已经有这本书了。
不过，那位楼主把一本书拆成了18个章节，每个章节收1个金币，这样既不方便下载、阅读。
为了方便大家，我这里提供一个全本下载，只要4个金币。
Data Mining for Business Applications
Edited by Longbing Cao
Philip S. Yu
Part I Domain Driven KDD Methodology
1 Introduction to Domain Driven Data Mining. 3
2 Post-processing Data Mining Models for Actionability. 11
3 On Mining Maximal Pattern-Based Clusters. . 31
4 Role of Human Intelligence in Domain Driven Data Mining. 53
5 Ontology Mining for Personalized Search. . 63
Part II Novel KDD Domains & Techniques
6 Data Mining Applications in Social Security. . 81
7 Security Data Mining: A Survey Introducing Tamper-Resistance. . 97
8 A Domain Driven Mining Algorithm on Gene Sequence Clustering. 111
9 Domain Driven Tree Mining of Semi-structured Mental Health Information. 127
10 Text Mining for Real-time Ontology Evolution. . 143
11 Microarray Data Mining: Selecting Trustworthy Genes with Gene Feature Ranking. 159
12 Blog Data Mining for Cyber Security Threats. 169
13 Blog Data Mining: The Predictive Power of Sentiments. 183
14 Web Mining: Extracting Knowledge from the WorldWideWeb. 197
15 DAG Mining for Code Compaction. . 209
16 A Framework for Context-Aware Trajectory Data Mining. . 225
17 Census Data Mining for Land Use Classification. . 241
18 Visual Data Mining for Developing Competitive Strategies in Higher Education. . 253
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