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Data Mining for Business Applications

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

04.11.2010

Herausgeber

Longbing Cao + weitere

Verlag

Springer Us

Seitenzahl

302

Maße (L/B/H)

23,5/15,5/1,8 cm

Gewicht

493 g

Auflage

Softcover reprint of hardcover 1st ed. 2009

Sprache

Englisch

ISBN

978-1-4419-4635-5

Beschreibung

Rezension

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)

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

04.11.2010

Herausgeber

Verlag

Springer Us

Seitenzahl

302

Maße (L/B/H)

23,5/15,5/1,8 cm

Gewicht

493 g

Auflage

Softcover reprint of hardcover 1st ed. 2009

Sprache

Englisch

ISBN

978-1-4419-4635-5

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: Data Mining for Business Applications
  • Produktbild: Data Mining for Business Applications
  • 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.