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Titlebook: Data Engineering; Mining, Information Yupo Chan,John Talburt,Terry M. Talley Book 2010 Springer-Verlag US 2010 Analytics.association.class

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書目名稱Data Engineering
副標(biāo)題Mining, Information
編輯Yupo Chan,John Talburt,Terry M. Talley
視頻videohttp://file.papertrans.cn/263/262784/262784.mp4
概述First volume to organize data mining, management, and warehousing into the systematic structure of Data Engineering.Focuses on recent applied research results applicable to a broad industry-research-a
叢書名稱International Series in Operations Research & Management Science
圖書封面Titlebook: Data Engineering; Mining, Information Yupo Chan,John Talburt,Terry M. Talley Book 2010 Springer-Verlag US 2010 Analytics.association.class
描述.DATA ENGINEERING: Mining, Information, and Intelligence. describes applied research aimed at the task of collecting data and distilling useful information from that data. Most of the work presented emanates from research completed through collaborations between Acxiom Corporation and its academic research partners under the aegis of the Acxiom Laboratory for Applied Research (ALAR). Chapters are roughly ordered to follow the logical sequence of the transformation of data from raw input data streams to refined information. Four discrete sections cover Data Integration and Information Quality; Grid Computing; Data Mining; and Visualization. Additionally, there are exercises at the end of each chapter....The primary audience for this book is the broad base of anyone interested in data engineering, whether from academia, market research firms, or business-intelligence companies. The volume is ideally suited for researchers, practitioners, and postgraduate students alike. With its focus on problems arising from industry rather than a basic research perspective, combined with its intelligent organization, extensive references, and subject and author indices, it can serve the academic, r
出版日期Book 2010
關(guān)鍵詞Analytics; association; classification; data quality; database; entity resolution; grid computing; performa
版次1
doihttps://doi.org/10.1007/978-1-4419-0176-7
isbn_softcover978-1-4614-2476-5
isbn_ebook978-1-4419-0176-7Series ISSN 0884-8289 Series E-ISSN 2214-7934
issn_series 0884-8289
copyrightSpringer-Verlag US 2010
The information of publication is updating

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Semantic Data Matching: Principles and Performance, Simple string matching algorithms, such as dynamic programming, can handle typographical errors in the data, but are less able to match records that require contextual and experiential knowledge. Latent Semantic Indexing (LSI) (Berry et al. ; Deerwester et al. is a machine intelligence technique th
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Application of the Near Miss Strategy and Edit Distance to Handle Dirty Data,hods vary from source to source by format, volume, and media type. Therefore, it is advantageous to deploy customized data hygiene techniques to standardize the data for meaningfulness and usefulness based on the organization.
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Parallel File Systems,ound the simultaneous movement and transformation of data on many compute elements. Effective storage solutions combine hardware and software to meet these needs. The storage hardware selected must provide enough raw throughput for the expected workloads. Typical storage hardware architectures also
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Performance Modeling of Enterprise Grids,l and open source, is widely used as a guide for the development of new systems and the upgrading of exiting ones. Tools such as queuing network models, stochastic Petri nets, and event driven simulation are in common use for stand-alone computer systems and networks. Unfortunately, no set of compre
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Delay Characteristics of Packet Switched Networks,ing the way people do computing and manage information. These new technologies have enabled the utilization of a wide variety of geographically distributed computational resources, including computers, storage systems, data sources, and special devices, as a unified resource. This new paradigm is po
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