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Data Engineering: Mining, Information and Intelligence: International Series in Operations Research & Management Science, cartea 132

Editat de Yupo Chan, John Talburt, Terry M. Talley
en Limba Engleză Paperback – 25 feb 2012
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, research, and industrial audiences.
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Specificații

ISBN-13: 9781461424765
ISBN-10: 1461424763
Pagini: 468
Ilustrații: XVII, 447 p.
Dimensiuni: 155 x 235 x 25 mm
Greutate: 0.65 kg
Ediția:2010
Editura: Springer Us
Colecția Springer
Seria International Series in Operations Research & Management Science

Locul publicării:New York, NY, United States

Public țintă

Research

Cuprins

A Declarative Approach to Entity Resolution.- Transitive Closure of Data Records: Application and Computation.- Semantic Data Matching: Principles and Performance.- Application of the Near Miss Strategy and Edit Distance to Handle Dirty Data.- A Parallel General-Purpose Synthetic Data Generator1.- A Grid Operating Environment for CDI.- Parallel File Systems.- Performance Modeling of Enterprise Grids.- Delay Characteristics of Packet Switched Networks.- Knowledge Discovery in Textual Databases: A Concept-Association Mining Approach.- Mining E-Documents to Uncover Structures.- Designing a Flexible Framework for a Table Abstraction.- Information Quality Framework for Verifiable Intelligence Products.- Interactive Visualization of Large High-Dimensional Datasets.- Image Watermarking Based on Pyramid Decomposition with CH Transform.- Immersive Visualization of Cellular Structures.- Visualization and Ontology of Geospatial Intelligence.- Looking Ahead.

Textul de pe ultima copertă

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, research, and industrial audiences.

Caracteristici

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-academic market End-of-chapter exercises for classroom use Includes supplementary material: sn.pub/extras