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Search-Based Applications

Book Description

We are poised at a major turning point in the history of information management via computers. Recent evolutions in computing, communications, and commerce are fundamentally reshaping the ways in which we humans interact with information, and generating enormous volumes of electronic data along the way. As a result of these forces, what will data management technologies, and their supporting software and system architectures, look like in ten years? It is difficult to say, but we can see the future taking shape now in a new generation of information access platforms that combine strategies and structures of two familiar -- and previously quite distinct -- technologies, search engines and databases, and in a new model for software applications, the Search-Based Application (SBA), which offers a pragmatic way to solve both well-known and emerging information management challenges as of now. Search engines are the world's most familiar and widely deployed information access tool, used by hundreds of millions of people every day to locate information on the Web, but few are aware they can now also be used to provide precise, multidimensional information access and analysis that is hard to distinguish from current database applications, yet endowed with the usability and massive scalability of Web search. In this book, we hope to introduce Search Based Applications to a wider audience, using real case studies to show how this flexible technology can be used to intelligently aggregate large volumes of unstructured data (like Web pages) and structured data (like database content), and to make that data available in a highly contextual, quasi real-time manner to a wide base of users for a varied range of purposes. We also hope to shed light on the general convergences underway in search and database disciplines, convergences that make SBAs possible, and which serve as harbingers of information management paradigms and technologies to come. Table of Contents: Search Based Applications / Evolving Business Information Access Needs / Origins and Histories / Data Models and Storage / Data Collection/Population / Data Processing / Data Retrieval / Data Security, Usability, Performance, Cost / Summary Evolutions and Convergences / SBA Platforms / SBA Uses and Preconditions / Anatomy of a Search Based Application / Case Study: GEFCO / Case Study: Urbanizer / Case Study: National Postal Agency / Future Directions

Table of Contents

  1. Cover
  2. Synthesis Lectures on Information Concepts, Retrieval, and Services
  3. Copyright
  4. Title Page
  5. Acknowledgments
  6. Glossary
  7. 1 Search Based Applications
    1. 1.1 Introduction
      1. 1.1.1 What is a Search Based Application?
    2. 1.2 High Impact, Low Risk Solution for Businesses
    3. 1.3 Fertile Ground for Interdisciplinary Research
    4. 1.4 A Valuable Tool for Database Administrators
    5. 1.5 New Opportunities for Search Specialists
    6. 1.6 New Flexibility for Software Developers
      1. 1.6.1 Lecture Roadmap
  8. 2 Evolving Business Information Access Needs
    1. 2.1 Changing Times
    2. 2.2 The Need for High Performance and Scalability
    3. 2.3 The Need for Unified Access to Global Information
    4. 2.4 The Need for Simple Yet Secure Access
  9. 3 Origins and Histories
    1. 3.1 Search Engines
    2. 3.2 Databases
    3. 3.3 What has Changed Recently
      1. 3.3.1 Search Engines Enter the Enterprise
      2. 3.3.2 Databases Go Online
      3. 3.3.3 Structural and Conceptual Changes
  10. 4 Data Models & Storage
    1. 4.1 Search Engines
      1. 4.1.1 Conceptual Data Model
      2. 4.1.2 Data Storage
      3. 4.1.3 Storage Framework
    2. 4.2 Databases
      1. 4.2.1 Conceptual Data Model
      2. 4.2.2 Data Storage
      3. 4.2.3 Storage Framework
    3. 4.3 What has Changed Recently
      1. 4.3.1 Search Engines
      2. 4.3.2 Databases
  11. 5 Data Collection/Population
    1. 5.1 Search Engines
      1. 5.1.1 Collection
      2. 5.1.2 Updating
    2. 5.2 Databases
      1. 5.2.1 Creation/Collection
      2. 5.2.2 Updating
    3. 5.3 What has Changed
      1. 5.3.1 Search Engines
      2. 5.3.2 Databases
  12. 6 Data Processing
    1. 6.1 Search Engines
      1. 6.1.1 Natural Language Processing
      2. 6.1.2 Relevancy Criteria
    2. 6.2 Databases
    3. 6.3 What has Changed
      1. 6.3.1 Search Engines
      2. 6.3.2 Databases
  13. 7 Data Retrieval
    1. 7.1 Search Engines
      1. 7.1.1 Querying
      2. 7.1.2 Output
    2. 7.2 Databases
      1. 7.2.1 Querying
      2. 7.2.2 Output
    3. 7.3 What’s Changed?
      1. 7.3.1 Search Engines
      2. 7.3.2 Databases
  14. 8 Data Security, Usability, Performance, Cost
    1. 8.1 Search Engines
    2. 8.2 Databases
    3. 8.3 What has Changed
      1. 8.3.1 Search Engines
  15. 9 Summary Evolutions and Convergences
    1. 9.1 SBA-Enabling Search Engine Evolutions
      1. 9.1.1 Data Model
      2. 9.1.2 Data Storage
      3. 9.1.3 Data Collection
      4. 9.1.4 Data Processing
      5. 9.1.5 Data Retrieval & Output
      6. 9.1.6 Data Security, Usability, Performance, Cost
    2. 9.2 Convergence
  16. 10 SBA Platforms
    1. 10.1 What is an SBA Platform?
    2. 10.2 Information Access Platforms
    3. 10.3 SBA Platforms: Market Leaders
    4. 10.4 SBA Platforms: Other Vendors
    5. 10.5 SBA Vendors: COTS Applications
  17. 11 SBA Uses & Preconditions
    1. 11.1 When Are SBAs Used?
    2. 11.2 How Are SBAs Used?
  18. 12 Anatomy of a Search Based Application
    1. 12.1 SBAs for Structured Data
      1. 12.1.1 Data Collection
      2. 12.1.2 Data Processing
      3. 12.1.3 Data Updates
      4. 12.1.4 Data Retrieval & Analysis
    2. 12.2 SBAs for Unstructured Content
      1. 12.2.1 Data Collection
      2. 12.2.2 Data Processing
      3. 12.2.3 Data Updates
      4. 12.2.4 Data Retrieval & Analysis
    3. 12.3 SBAs for Hybrid Content
  19. 13 Case Study: GEFCO
    1. 13.1 Background
    2. 13.2 A Track & Trace Solution
    3. 13.3 Existing Drawbacks
    4. 13.4 Opting for a Search Based Application
    5. 13.5 First prototypes
    6. 13.6 Deployment
    7. 13.7 Future
  20. 14 Case Study: Urbanizer
    1. 14.1 Background
    2. 14.2 The Urbanizer Solution
    3. 14.3 How Urbanizer Works
    4. 14.4 What’s Next
  21. 15 Case Study: National Postal Agency
    1. 15.1 Customer Service SBA
      1. 15.1.1 Background
      2. 15.1.2 Deployment
    2. 15.2 Operational Business Intelligence (OBI) SBA
      1. 15.2.1 Background
      2. 15.2.2 Deployment
    3. 15.3 Sales Information SBA for Telemarketing
      1. 15.3.1 Background
      2. 15.3.2 Deployment
  22. 16 Future Directions
    1. 16.1 The Influence of the Deep Web
      1. 16.1.1 Surfacing Structured Data
      2. 16.1.2 Opening Access to Multimedia Content
    2. 16.2 The Influence of the Semantic Web
    3. 16.3 The Influence of the Mobile Web
      1. 16.3.1 Mission-Based IR
      2. 16.3.2 Innovation in Visualization
    4. 16.4 And Continuing Database/Search Convergence
  23. Bibliography
  24. Authors’ Biographies
  25. Index