Data Mining for Business Applications


ISBN: 978-0-387-79419-8 (Print) 978-0-387-79420-4 (Online)
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Table of contents (20 chapters)

  1. Front Matter

    Pages i-xix

  2. Domain Driven KDD Methodology

    1. Book Chapter

      Pages 3-10

      Introduction to Domain Driven Data Mining

    2. Book Chapter

      Pages 11-30

      Post-processing Data Mining Models for Actionability

    3. Book Chapter

      Pages 31-52

      On Mining Maximal Pattern-Based Clusters

    4. Book Chapter

      Pages 53-61

      Role of Human Intelligence in Domain Driven Data Mining

    5. Book Chapter

      Pages 63-78

      Ontology Mining for Personalized Search

  3. Novel KDD Domains & Techniques

    1. Book Chapter

      Pages 81-96

      Data Mining Applications in Social Security

    2. Book Chapter

      Pages 97-110

      Security Data Mining: A Survey Introducing Tamper-Resistance

    3. Book Chapter

      Pages 111-126

      A Domain Driven Mining Algorithm on Gene Sequence Clustering

    4. Book Chapter

      Pages 127-141

      Domain Driven Tree Mining of Semi-structured Mental Health Information

    5. Book Chapter

      Pages 143-157

      Text Mining for Real-time Ontology Evolution

    6. Book Chapter

      Pages 159-168

      Microarray Data Mining: Selecting Trustworthy Genes with Gene Feature Ranking

    7. Book Chapter

      Pages 169-182

      Blog Data Mining for Cyber Security Threats

    8. Book Chapter

      Pages 183-195

      Blog Data Mining: The Predictive Power of Sentiments

    9. Book Chapter

      Pages 197-208

      Web Mining: Extracting Knowledge from the World Wide Web

    10. Book Chapter

      Pages 209-223

      DAG Mining for Code Compaction

    11. Book Chapter

      Pages 225-239

      A Framework for Context-Aware Trajectory

    12. Book Chapter

      Pages 241-251

      Census Data Mining for Land Use Classification

    13. Book Chapter

      Pages 253-266

      Visual Data Mining for Developing Competitive Strategies in Higher Education

    14. Book Chapter

      Pages 267-282

      Data Mining For Robust Flight Scheduling

    15. Book Chapter

      Pages 283-295

      Data Mining for Algorithmic Asset Management

  4. Back Matter

    Pages 297-302