Data Mining for Business Applications
Overview
Domain Driven KDD Methodology.- to Domain Driven Data Mining.- Post-processing Data Mining Models for Actionability.- On Mining Maximal Pattern-Based Clusters.- Role of Human Intelligence in Domain Driven Data Mining.- Ontology Mining for Personalized Search.- Novel KDD Domains & Techniques.- Data Mining Applications in Social Security.- Security Data Mining: A Survey Introducing Tamper-Resistance.- A Domain Driven Mining Algorithm on Gene Sequence Clustering.- Domain Driven Tree Mining of Semi-structured Mental Health Information.- Text Mining for Real-time Ontology Evolution.- Microarray Data Mining: Selecting Trustworthy Genes with Gene Feature Ranking.- Blog Data Mining for Cyber Security Threats.- Blog Data Mining: The Predictive Power of Sentiments.- Web Mining: Extracting Knowledge from the World Wide Web.- DAG Mining for Code Compaction.- A Framework for Context-Aware Trajectory.- Census Data Mining for Land Use Classification.- Visual Data Mining for Developing Competitive Strategies in Higher Education.- Data Mining For Robust Flight Scheduling.- Data Mining for Algorithmic Asset Management.
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Details
- ISBN-13: 9780387794198
- ISBN-10: 0387794190
- Publisher: Springer
- Publish Date: October 2008
- Dimensions: 9.21 x 6.14 x 0.75 inches
- Shipping Weight: 1.39 pounds
- Page Count: 302
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