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Visual Analytics and Interactive Technologies

Book Description

Visual Analytics and Interactive Technologies: Data, Text and Web Mining Applications is a comprehensive reference on concepts, algorithms, theories, applications, software, and visualization of data mining, text mining, Web mining and computing/supercomputing. This publication provides a coherent set of related works on the state-of-the-art of the theory and applications of mining, making it a useful resource for researchers, practitioners, professionals and intellectuals in technical and non-technical fields.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Editorial Advisory Board and List of Reviewers
    1. List of Reviewers
  5. Preface
  6. Acknowledgment
  7. Section 1: Concepts, Algorithms, and Theory
    1. Chapter 1: Towards the Notion of Typical Documents in Large Collections of Documents
      1. Abstract
      2. INTRODUCTION
      3. BACKGROUND AND MOTIVATION
      4. GNGRANK
      5. EXPERIMENTS
      6. CONCLUSION
      7. FURTHER RESEARCH
    2. Chapter 2: Data Mining Techniques for Outlier Detection
      1. ABSTRACT
      2. INTRODUCTION
      3. RESEARCH ISSUES IN OUTLIER DETECTION
      4. CURRENT RESEARCH TRENDS
      5. EXPERIMENTAL RESULTS
      6. CONCLUSION AND FUTURE DIRECTIONS
    3. Chapter 3: Using an Ontology-Based Framework to Extract External Web Data for the Data Warehouse
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. MAIN FOCUS OF THE CHAPTER
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
    4. Chapter 4: Dimensionality Reduction for Interactive Visual Clustering
      1. Abstract
      2. INTRODUCTION
      3. BACKGROUND
      4. VISUAL CLUSTERING: ISSUES AND CHALLENGES
      5. DIMENSIONALITY REDUCTION FOR VISUAL CLUSTERING
      6. EXPERIMENTAL ANALYSIS AND DISCUSSION
      7. CONCLUSION
      8. FURTHER RESEARCH DIRECTION
    5. Chapter 5: Database Analysis with ANNs by means of Graph Evolution
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. ANN DEVELOPMENT WITH GRAPH EVOLUTION
      5. RESULTS
      6. CONCLUSION
      7. FUTURE TRENDS
    6. Chapter 6: An Optimal Categorization of Feature Selection Methods for Knowledge Discovery
      1. ABSTRACT
      2. INTRODUCTION
      3. REVIEW OF FEATURE SELECTION APPROACHES
      4. FEATURE SELECTION ALGORITHMS
      5. RESULTS
      6. CONCLUSION
    7. Chapter 7: From Data to Knowledge
      1. ABSTRACT
      2. INTRODUCTION
      3. DATA MINING TASKS
      4. DATABASE VS DATA MINING
      5. DATA MINING APPLICATIONS
  8. Section 2: Applications of Mining and Visualizations
    1. Chapter 8: Patent Infringement Risk Analysis Using Rough Set Theory
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. MAIN FOCUS OF THE CHAPTER
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
    2. Chapter 9: Visual Survey Analysis in Marketing
      1. ABSTRACT
      2. BACKGROUND
      3. ORDEVAL APPROACH
      4. FUTURE RESEARCH DIRECTIONS
      5. CONCLUSION
    3. Chapter 10: Assessing Data Mining Approaches for Analyzing Actuarial Student Success Rate
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. ANALYSIS OF ACTUARIAL SUCCESS RATE
      5. RESULTS
      6. CONCLUSION AND FUTURE RESEARCH
    4. Chapter 11: A Robust Biclustering Approach for Effective Web Personalization
      1. Abstract
      2. 1. INTRODUCTION
      3. 2. BACKGROUND
      4. 3. METHODOLOGY
      5. 4. RELATED WORK
      6. 5. EXPERIMENTAL EVALUATION
      7. 6. FUTURE RESEARCH DIRECTIONS
      8. 7. CONCLUSION
    5. Chapter 12: Web Mining and Social Network Analysis
      1. ABSTRACT
      2. INTRODUCTION
      3. SOCIAL NETWORK ANALYSIS
      4. MINING TECHNIQUES
      5. COMBINED APPROACH
      6. APPLICATIONS
      7. FURTHER CHALLENGES
      8. CONCLUSIONS
  9. Section 3: Visual Systems, Software and Supercomputing
    1. Chapter 13: iVAS
      1. Abstract
      2. INTRODUCTION
      3. BACKGROUND
      4. iVAS: AN INTERACTIVE VISUAL ANALYTIC SYSTEM
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
    2. Chapter 14: Mammogram Mining Using Genetic Ant-Miner
      1. ABSTRACT
      2. INTRODUCTION
      3. METHODS AND MATERIALS
      4. IMAGE PREPROCESSING
      5. FEATURE EXTRACTION
      6. DISCRETIZATION
      7. CLASSIFICATION OF MAMMOGRAMS
      8. COMPARATIVE STUDY
      9. GENETIC ANT-MINER
      10. GENETIC ALGORITHMS
      11. COMPUTATIONAL RESULTS
      12. COMPARATIVE STUDY
      13. CONCLUSION
      14. FURTHER RESEARCH DIRECTION
    3. Chapter 15: Use of SciDBMaker as Tool for the Design of Specialized Biological Databases
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. SCIENTIFIC DATABASE MAKER, A COMPREHENSIVE TOOL FOR THE DESIGN OF SPECIALIZED BIOLOGICAL DATABASES
      5. WHAT NEXT: WEB INTERFACE DESIGN AND TOOLS IMPLEMENTATION
      6. CONCLUSION
    4. Chapter 16: Interactive Visualization Tool for Analysis of Large Image Databases
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. MULTIPLE VIEWS INTERFACE
      5. CONCLUSION
    5. Chapter 17: Supercomputers and Supercomputing
      1. ABSTRACT
      2. INTRODUCTION
      3. CONCLUSION
  10. Compilation of References
  11. About the Contributors
  12. Index