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Data Engineering

Mining, Information and Intelligence

  • Book
  • © 2010

Overview

Editors:
  1. Yupo Chan

    1. Dept. Systems Engineering, Donaghey College of Info Sci., University of Arkansas, Little Rock, USA

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  2. John Talburt

    1. Dept. Information Science, University of Arkansas, Little Rock, Little Rock, USA

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    You can also search for this editor in PubMed   Google Scholar

  3. Terry M. Talley

    1. Acxiom Corporation, Conway, USA

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    You can also search for this editor in PubMed   Google Scholar

  • 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

Part of the book series: International Series in Operations Research & Management Science (ISOR, volume 132)

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Table of contents (19 chapters)

  1. Front Matter

    Pages i-xvi
    Download chapter PDF

  2. Introduction

    • Terry M. Talley, John R. Talburt, Yupo Chan
    Pages 1-16

  3. A Declarative Approach to Entity Resolution

    • Tanton H. Gibbs
    Pages 17-38

  4. Transitive Closure of Data Records: Application and Computation

    • Wing Ning Li, Roopa Bheemavaram, Xiaojun Zhang
    Pages 39-75

  5. Semantic Data Matching: Principles and Performance

    • Russell Deaton, Thao Doan, Tom Schweiger
    Pages 77-90

  6. Application of the Near Miss Strategy and Edit Distance to Handle Dirty Data

    • Cihan Varol, Coskun Bayrak, Rick Wagner, Dana Goff
    Pages 91-101

  7. A Parallel General-Purpose Synthetic Data Generator1

    • Joseph E. Hoag, Craig W. Thompson
    Pages 103-117

  8. A Grid Operating Environment for CDI

    • Terry M. Talley
    Pages 119-142

  9. Parallel File Systems

    • Robert Ross, Philip Carns, David Metheny
    Pages 143-168

  10. Performance Modeling of Enterprise Grids

    • Doug L. Hoffman, Amy Apon, Larry Dowdy, Baochuan Lu, Nathan Hamm, Linh Ngo et al.
    Pages 169-201

  11. Delay Characteristics of Packet Switched Networks

    • Qiang Duan
    Pages 203-223

  12. Knowledge Discovery in Textual Databases: A Concept-Association Mining Approach

    • Mutlu Mete, Nurcan Yuruk, Xiaowei Xu, Daniel Berleant
    Pages 225-243

  13. Mining E-Documents to Uncover Structures

    • Azita Bahrami
    Pages 245-278

  14. Designing a Flexible Framework for a Table Abstraction

    • H. Conrad Cunningham, Yi Liu, Jingyi Wang
    Pages 279-314

  15. Information Quality Framework for Verifiable Intelligence Products

    • Hongwei Zhu, Richard Y. Wang
    Pages 315-333

  16. Interactive Visualization of Large High-Dimensional Datasets

    • Wei Ding, Ping Chen
    Pages 335-351

  17. Image Watermarking Based on Pyramid Decomposition with CH Transform

    • R. Kountchev, M. Milanova, Vl. Todorov, R. Kountcheva
    Pages 353-387

  18. Immersive Visualization of Cellular Structures

    • Sinan Kockara, Nawab Ali, Serhan Dagtas
    Pages 389-402

  19. Visualization and Ontology of Geospatial Intelligence

    • Yupo Chan
    Pages 403-429

  20. Looking Ahead

    • Yupo Chan, John Talburt, Terry Talley
    Pages 431-439
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Keywords

About this book

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.

Editors and Affiliations

  • Dept. Systems Engineering, Donaghey College of Info Sci., University of Arkansas, Little Rock, USA

    Yupo Chan

  • Dept. Information Science, University of Arkansas, Little Rock, Little Rock, USA

    John Talburt

  • Acxiom Corporation, Conway, USA

    Terry M. Talley

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