Sinopsis
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.
"Sinopsis" puede pertenecer a otra edición de este libro.
De la contraportada
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.
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Domain Driven Data Mining
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Domain Driven Data Mining
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Springer US Dez 2014, 2014
ISBN 10: 1489985077
ISBN 13: 9781489985071
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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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
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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
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Domain Driven Data Mining
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Springer US, Springer US Dez 2014, 2014
ISBN 10: 1489985077
ISBN 13: 9781489985071
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Data mining has emerged as one of the most active areas in information and c- munication technologies(ICT). With the boomingof the global economy,and ub- uitouscomputingandnetworkingacrosseverysectorand business,data andits deep analysis becomes a particularly important issue for enhancing the soft power of an organization, its production systems, decision-making and performance. The last ten years have seen ever-increasingapplications of data mining in business, gove- ment, social networks and the like. However, a crucial problem that prevents data mining from playing a strategic decision-support role in ICT is its usually limited decision-support power in the real world. Typical concerns include its actionability, workability, transferability, and the trustworthy, dependable, repeatable, operable and explainable capabilities of data mining algorithms, tools and outputs. This monograph, Domain Driven Data Mining, is motivated by the real-world challenges to and complexities of the current KDD methodologies and techniques, which are critical issues faced by data mining, as well as the ndings, thoughts and lessons learned in conducting several large-scale real-world data mining bu- ness applications. The aim and objective of domain driven data mining is to study effective and ef cient methodologies, techniques, tools, and applications that can discover and deliver actionable knowledge that can be passed on to business people for direct decision-making and action-taking.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 264 pp. Englisch. Nº de ref. del artículo: 9781489985071
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Domain Driven Data Mining
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Springer US, Springer US, 2014
ISBN 10: 1489985077
ISBN 13: 9781489985071
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
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
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