You are previewing Knowledge Discovery Practices and Emerging Applications of Data Mining: Trends and New Domains.
O'Reilly logo
Knowledge Discovery Practices and Emerging Applications of Data Mining: Trends and New Domains

Book Description

Knowledge Discovery Practices and Emerging Applications of Data Mining: Trends and New Domains introduces the reader to recent research activities in the field of data mining. This book covers association mining, classification, mobile marketing, opinion mining, microarray data mining, internet mining and applications of data mining on biological data, telecommunication and distributed databases, among others, while promoting understanding and implementation of data mining techniques in emerging domains.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Editorial Advisory Board and List of Reviewers
    1. Editorial Advisory Board
    2. List of Reviewers
  5. Foreword
  6. Preface
    1. WHERE THE BOOK STANDS
    2. ORGANIZATION OF CHAPTERS
    3. CONCLUSION
  7. Acknowledgment
  8. Section 1: Concepts, Tools and Techniques
    1. Chapter 1: A Framework to Detect Disguised Missing Data
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. A FRAMEWORK TO DETECT DISGUISED MISSING DATA
      5. PROBLEMS WITH THE CURRENT FRAMEWORK
      6. SOLUTIONS AND RECOMMENDATIONS
      7. EXPERIMENTAL RESULTS
      8. FUTURE RESEARCH DIRECTIONS
      9. CONCLUSION
    2. Chapter 2: Microarray Data Mining
      1. Abstract
      2. INTRODUCTION
      3. DATA MINING TECHNIQUES FOR MICROARRAY
      4. FUTURE RESEARCH DIRECTIONS
      5. CONCLUSION
    3. Chapter 3: Temporal Association Rule Mining in Large Databases
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. Temporal Data Mining
      5. TECHNIQUE USED FOR FINDING FREQUENT TEMPORAL ITEMSETS
      6. CONCLUSION
    4. Chapter 4: Optimizing and Managing Digital Telecommunication Systems Using Data Mining and Knowledge Discovery Approaches
      1. ABSTRACT
      2. INTRODUCTION
      3. DATA MINING AND KNOWLEDGE DISCOVERY PROCESS
      4. USING THE KNOWLEDGE DISCOVERY PROCESS FOR DETECTING AN ERROR IN ESS SWITCH: CASE STUDY
      5. APPLICATION OF DATA MINING AND KNOWLEDGE DISCOVERY PROCESS IN ANALYZING THE QoS ISSUES
      6. CONCULSION
    5. Chapter 5: Finding Persistent Strong Rules
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. ASSOCIATION PLUS CLASSIFICATION: PERSISTENT STRONG RULES
      5. MINING THE ANES DATA
      6. FUTURE RESEARCH DIRECTIONS
      7. CONCLUSION
      8. APPENDIX
  9. Section 2: Research and Learning
    1. Chapter 6: A Perspective on Data Mining Integration with Business Intelligence
      1. Abstract
      2. INTRODUCTION
      3. A FRAMEWORK FOR BUSINESS INTELLIGENCE
      4. DATA MINING AND KNOWLEDGE DISCOVERY IN DATABASES
      5. DM INTEGRATION WITH RELATIONAL DATABASES
      6. INTEGRATING DATA MINING WITH BUSINESS INTELLIGENCE
      7. FUTURE RESEARCH DIRECTIONS
      8. CONCLUSION
    2. Chapter 7: Shadow Sensitive SWIFT
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. DISTRIBUTED REAL-TIME DATABASE SYSTEM MODEL
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
    3. Chapter 8: Mobile Marketing
      1. Abstract
      2. INTRODUCTION
      3. CHALLENGES IN THE MANAGEMENT OF MOBILE VAS SYSTEMS
      4. CUSTOMER CLUSTERING
      5. LEARNING ON NEW OFFERS
      6. TARGETING USERS AND OFFER DESIGN
      7. FUTURE RESEARCH DIRECTIONS
      8. CONCLUSION
    4. Chapter 9: Data Mining System Execution Traces to Validate Distributed System Quality-of-Service Properties
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. MOTIVATIONAL CASE STUDY: THE QED PROJECT
      5. DATA MINING SYSTEM EXECUTION TRACES USING DATA FLOW MODELS
      6. EXPERIMENTAL RESULTS
      7. FUTURE RESEARCH DIRECTIONS
      8. CONCLUSION
    5. Chapter 10: Cooperation Between Expert Knowledge and Data Mining Discovered Knowledge
      1. Abstract
      2. INTRODUCTION
      3. BACKGROUND
      4. COOPERATION BETWEEN EXPERT KNOWLEDGE AND DISCOVERED KNOWLEDGE: AUTHORS EXPERIENCE IN THE FIELD OF ISOKINETICS
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
  10. Section 3: Case Studies
    1. Chapter 11: A Comparative Study of Associative Classifiers in Mesenchymal Stem Cell Differentiation Analysis
      1. Abstract
      2. INTRODUCTION
      3. BACKGROUND
      4. FIVE ASSOCIATIVE CLASSIFICATION APPROACHES
      5. DATA PREPARATION
      6. EXPERIMENTS
      7. FUTURE RESEARCH DIRECTIONS
      8. CONCLUSION
    2. Chapter 12: Multiagent Knowledge-Based System Accessing Distributed Resources on Knowledge Grid
      1. Abstract
      2. INTRODUCTION
      3. WWW, SEMANTIC WEB, DATA GRID AND KNOWLEDGE GRID
      4. KNOWLEDGE GRID
      5. TYPICAL APPLICATIONS AND WORK DONE SO FAR
      6. MULTIAGENT SYSTEM APPLICATION MINING KNOWLEDGE GRID
      7. CONCLUSION
    3. Chapter 13: Opinion Mining with SentiWordNet
      1. Abstract
      2. INTRODUCTION
      3. OPINION MINING
      4. SENTIMENT CLASSIFICATION WITH SENTIWORDNET
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
    4. Chapter 14: Analysis and Integration of Biological Data
      1. Abstract
      2. INTRODUCTION
      3. NEW TRENDS
      4. BACKGROUND
      5. Clustering Validation for the Comparison of Algorithms
      6. Pipeline for Integration and Analysis of Introgression Lines
      7. FUTURE RESEARCH DIRECTIONS
      8. CONCLUSION
    5. Chapter 15: Internet Forums
      1. Abstract
      2. INTRODUCTION
      3. LITERATURE OVERVIEW
      4. MINING INTERNET FORUMS
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
  11. Compilation of References
  12. About the Contributors