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Advanced Data Mining Tools and Methods for Social Computing - Research Book

Advanced Data Mining Tools and Methods for Social Computing - Research Book

Hot Research Book in Advanced Data Mining Tools and Methods for Social Computing

Author(s) Name:  Sourav De, Sandip Dey, Siddhartha Bhattacharyya, Surbhi Bhatia

About the Book:

   Advanced Data Mining Tools and Methods for Social Computing explores advances in the latest data mining tools, methods, algorithms and the architectures being developed specifically for social computing and social network analysis. The book reviews major emerging trends in technology that are supporting current advancements in social networks, including data mining techniques and tools. It also aims to highlight the advancement of conventional approaches in the field of social networking. Chapter coverage includes reviews of novel techniques and state-of-the-art advances in the area of data mining, machine learning, soft computing techniques, and their applications in the field of social network analysis.

Key Features

  • Provides insights into the latest research trends in social network analysis
  • Covers a broad range of data mining tools and methods for social computing and analysis
  • Includes practical examples and case studies across a range of tools and methods
  • Features coding examples and supplementary data sets in every chapter

  • Table of Contents

  • Chapter 1: An introduction to data mining in social networks
  •   1.1. Data mining concepts
      1.2. Social computing
      1.3. Clustering and classification
  • Chapter 2: Performance tuning of Android applications using clustering and optimization heuristics
  •   2.1. Introduction
      2.2. Research methodology
      2.3. Subject applications
      2.4. Implementation phase 1 – clustering and knapsack solvers
      2.5. Implementation phase 2 – Ant colony optimization
  • Chapter 3: Sentiment analysis of social media data evolved from COVID-19 cases – Maharashtra
  •   3.1. Introduction
      3.2. Literature review
      3.3. Proposed design
      3.4. Analysis and predictions
  • Chapter 4: COVID-19 outbreak analysis and prediction using statistical learning
  •   4.1. Introduction
      4.2. Related literature
      4.3. Proposed model
  • Chapter 5: Verbal sentiment analysis and detection using recurrent neural network
  •   5.1. Introduction
      5.2. Sources for sentiment detection
      5.3. Literature survey
      5.4. Machine learning techniques for sentiment analysis
  • Chapter 6: A machine learning approach to aid paralysis patients using EMG signals
  •   6.1. Introduction
      6.2. Associated works
      6.3. System model
  • Chapter 7: Influence of traveling on social behavior
  •   7.1. Introduction
      7.2. Importance of social networking in real life
      7.3. Dynamics of traveling
      7.4. Dynamics-based social behavior analysis
  • Chapter 8: A study on behavior analysis in social network
  •   8.1. Basic concepts of behavior analysis in social networks
      8.2. Uses of behavior analysis in social networks
  • Chapter 9: Recent trends in recommendation systems and sentiment analysis
  •   9.1. Basic terms and concepts of sentiment analysis and recommendation systems
      9.2. Overview of sentiment analysis approaches in recommendation systems
  • Chapter 10: Data visualization: existing tools and techniques
  •   10.1. Prior research works on data visualization issues
      10.2. Challenges during visualization of innumerable data
      10.3. Existing data visualization tools and techniques with key characteristics
  • Chapter 11: An intelligent agent to mine for frequent patterns in uncertain graphs
  •   11.1. Introduction
      11.2. Mining graphs and uncertainty
      11.3. Methodology
      11.4. Implementation
  • Chapter 12: Mining challenges in large-scale IoT data framework – a machine learning perspective
  •   12.1. Proposed work
      12.2. Application framework
      12.3. H2O work flow environment
  • Chapter 13: Conclusion
  • ISBN:  9780323857086

    Publisher:  Elsevier

    Year of Publication:  2022

    Book Link:  Home Page Url