Recommender Systems (eBook, PDF)

A Multi-Disciplinary Approach
Redaktion: Roy, Monideepa; Datta, Sujoy; Kar, Pushpendu

• Format: PDF

Produktbeschreibung

This book presents a multi-disciplinary approach for development of Recommender Systems. It explains different types of pertinent algorithms with their comparative analysis, and their role for different applications including case studies. It explains Big Data behind Recommender System, making good decision support systems, etc.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 278
• Erscheinungstermin: 19. Juni 2023
• Englisch
• ISBN-13: 9781000886269
• Artikelnr.: 67838616

Autorenporträt

Monideepa Roy, Pushpendu Kar, Sujoy Datta

Inhaltsangabe

1. Comparison of Different Machine Learning Algorithms to Classify Whether
or Not a Tweet Is about a Natural Disaster: A Simulation-Based Approach; 2.
An End-to-End Comparison among Contemporary Content-Based Recommendation
Methodologies; 3. Neural Network-Based Collaborative Filtering for
Recommender Systems; 4. Recommendation System and Big Data: Its Types and
Applications; 5. The Role of Machine Learning /AI in Recommender Systems;
6. A Recommender System Based on TensorFlow Framework; 7. A Marketing
Approach to Recommender Systems; 8. Applied Statistical Analysis in
Recommendation Systems; 9. An IoT-Enabled Innovative Smart Parking
Recommender Approach; 10. Classification of Road Segments in Intelligent
Traffic Management System; 11. Facial Gestures-Based Recommender System for
Evaluating Online Classes; 12. Application of Swarm Intelligence in
Recommender Systems; 13. Application of Machine-Learning Techniques in the
Development of Neighbourhood-Based Robust Recommender Systems; 14.
Recommendation Systems for Choosing Online Learning Resources: A Hands-On
Approach