Advanced Data Mining Tools and Methods for Social Computing

Advanced Data Mining Tools and Methods for Social Computing

De, Sourav
Dey, Sandip
Bhattacharyya, Siddhartha
Bhatia, Surbhi

136,24 €(IVA inc.)

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. 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 INDICE: 1. An Introduction to Data Mining in Social Networks 2. Performance Tuning of Android Applications using Clustering and Optimization Heuristics 3. Sentiment analysis of Social Media data evolved from COVID 19 cases - Maharashtra 4. COVID-19 Outbreak Analysis and Prediction Using Statisical Learning 5. Verbal Sentiment Analysis and Detection using Recurrent Neural Network 6. A Machine Learning approach to aid Paralysis patients using EMG signals 7. Influence of Travelling on Social Behaviour 8. A Study on Behaviour Analysis in Social Network 9. Recent Trends in Recommendation System using Sentiment Analysis 10. Data Visualization: Existing Tools and Techniques 11. An intelligent agent of Mining of Frequent Patterns on Uncertain Graphs 12. Mining Challenges in Large Scale IoT Data Framework - A Machine Learning Perspective 13. Conclusion

  • ISBN: 978-0-323-85708-6
  • Editorial: Academic Press
  • Encuadernacion: Rústica
  • Páginas: 292
  • Fecha Publicación: 20/01/2022
  • Nº Volúmenes: 1
  • Idioma: Inglés