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Data Mining for Business Applications Longbing Cao

Data Mining for Business Applications By Longbing Cao

Data Mining for Business Applications by Longbing Cao

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Summary

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.

Data Mining for Business Applications Summary

Data Mining for Business Applications by Longbing Cao

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-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 problems in theory and practice, and strengthen business intelligence in complex enterprise applications. The volume also explores challenges and directions for future research and development in the dialogue between academia and business.

Data Mining for Business Applications Reviews

From the reviews:

This is a compendium of papers written by 58 authors from different countries--including six from the US. ... present the full gamut of current research in the field of actionable knowledge discovery (AKD), as it applies to real-world problems. ... the intended audience of this book clearly includes industry practitioners, as well. ... The editors have culled a wide array of methodologies for and applications of data mining, from the cutting edge of research. This book provides ... further the development of actionable systems. (R. Goldberg, ACM Computing Reviews, June, 2009)

Table of Contents

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.

Additional information

NLS9781441946355
9781441946355
1441946357
Data Mining for Business Applications by Longbing Cao
Longbing Cao
New
Paperback
Springer-Verlag New York Inc.
2010-11-04
302
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
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Customer Reviews - Data Mining for Business Applications