From the reviews:
“This book offers a comprehensive discussion of domain-driven data mining (D3M), a set of techniques and methodologies that aim to discover actionable knowledge that can be presented to business decision makers in order to enable them to make informed decisions. ... The resulting approach is an exploration of possibilities for enhancing the decision-support power of data mining and knowledge discovery. ... This well-written and practical book summarizes domain-specific problem-solving methods for the delivery of actionable knowledge, and is suitable for researchers and students ... .” (Alessandro Berni, ACM Computing Reviews, November, 2010)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.
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Descripción Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 264 pp. Englisch. Nº de ref. del artículo: 9781489985071
Descripción Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Bridges the gap between business expectations and research outputIncludes techniques, methodologies and case studies in real-life enterprise dmAddresses new areas such as blog miningChallenges and Trends.- Methodology.- Ubiquitous I. Nº de ref. del artículo: 11466730
Descripción Condición: New. Nº de ref. del artículo: 22215391-n
Descripción Taschenbuch. Condición: Neu. 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. Nº de ref. del artículo: 9781489985071
Descripción Condición: New. 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. Num Pages: 264 pages, 50 black & white tables, biography. BIC Classification: KJQ; UNF; UNH. Category: (G) General (US: Trade). Dimension: 235 x 155 x 14. Weight in Grams: 409. . 2014. 2010th Edition. paperback. . . . . Nº de ref. del artículo: V9781489985071
Descripción Condición: New. 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. Num Pages: 264 pages, 50 black & white tables, biography. BIC Classification: KJQ; UNF; UNH. Category: (G) General (US: Trade). Dimension: 235 x 155 x 14. Weight in Grams: 409. . 2014. 2010th Edition. paperback. . . . . Books ship from the US and Ireland. Nº de ref. del artículo: V9781489985071