Domain Driven Data Mining
Language: English
Published by Springer, 2014
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Condition: New
US$ 143.97
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Add to basketItem description from seller
Druck auf Anfrage Neuware - Printed after ordering - In the present thriving global economy a need has evolved for complex data analysis to enhance an organization's production systems, decision-making tactics, and performance. In turn, data mining has emerged as one of the most active areas in information technologies. Domain Driven Data Mining offers state-of the-art research and development outcomes on methodologies, techniques, approaches and successful applications in domain driven, actionable knowledge discovery. About this book:Enhances the actionability and wider deployment of existing data-centered data mining through a combination of domain and business oriented factors, constraints and intelligence.Examines real-world challenges to and complexities of the current KDD methodologies and techniques.Details a paradigm shift from 'data-centered pattern mining' to 'domain driven actionable knowledge discovery' for next-generation KDD research and applications. Bridges the gap between business expectations and research output through detailed exploration of the findings, thoughts and lessons learned in conducting several large-scale, real-world data mining business applicationsIncludes techniques, methodologies and case studies in real-life enterprise data miningAddresses new areas such as blog miningDomain Driven Data Mining is suitable for researchers, practitioners and university students in the areas of data mining and knowledge discovery, knowledge engineering, human-computer interaction, artificial intelligence, intelligent information processing, decision support systems, knowledge management, and KDD project management.…
Seller Inventory # 9781489985071
- Title
- Domain Driven Data Mining
- Author
- Longbing Cao
- Publisher
- Springer
- Publication year
- 2014
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 1489985077
- ISBN 13
- 9781489985071
- Item weight
- 406 grams
- Dimensions
- 235x155x15 mm
This book offers state-of the-art research and development outcomes on methodologies, techniques, approaches and successful applications in domain driven, actionable knowledge discovery. It bridges the gap between business expectations and research output.
"Synopsis" may belong to another edition of this title.
From the Back Cover
In the present thriving global economy a need has evolved for complex data analysis to enhance an organization’s production systems, decision-making tactics, and performance. In turn, data mining has emerged as one of the most active areas in information technologies. Domain Driven Data Mining offers state-of the-art research and development outcomes on methodologies, techniques, approaches and successful applications in domain driven, actionable knowledge discovery.
About this book:
- Enhances the actionability and wider deployment of existing data-centered data mining through a combination of domain and business oriented factors, constraints and intelligence.
- Examines real-world challenges to and complexities of the current KDD methodologies and techniques.
- Details a paradigm shift from "data-centered pattern mining" to "domain driven actionable knowledge discovery" for next-generation KDD research and applications.
- Bridges the gap between business expectations and research output through detailed exploration of the findings, thoughts and lessons learned in conducting several large-scale, real-world data mining business applications
- Includes techniques, methodologies and case studies in real-life enterprise data mining
- Addresses new areas such as blog mining
Domain Driven Data Mining is suitable for researchers, practitioners and university students in the areas of data mining and knowledge discovery, knowledge engineering, human-computer interaction, artificial intelligence, intelligent information processing, decision support systems, knowledge management, and KDD project management.
"About the title" may belong to another edition of this title.
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