| 书目名称 | Domain Driven Data Mining | | 编辑 | Longbing Cao,Philip S. Yu,Yanchang Zhao | | 视频video | http://file.papertrans.cn/283/282505/282505.mp4 | | 概述 | Bridges the gap between business expectations and research output.Includes techniques, methodologies and case studies in real-life enterprise dm.Addresses new areas such as blog mining.Includes supple | | 图书封面 |  | | 描述 | .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 | | 出版日期 | Book 2010 | | 关键词 | data analysis; data mining; decision support system; information processing; knowledge discovery; knowled | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4419-5737-5 | | isbn_softcover | 978-1-4899-8507-1 | | isbn_ebook | 978-1-4419-5737-5 | | copyright | Springer-Verlag US 2010 |
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