-
Browse Book Series
- Adhesion and Adhesives: Fundamental and Applied Aspects
- Advances in Additive Manufacturing Technologies
- Advances in Antenna, Microwave and Communication Engineering
- Advances in Biofeedstocks and Biofuels
- Advances in Cyber Security
- Advances in Data Engineering and Machine Learning
- Advances in E-Mobility
- Advances in Hydrogen Production and Storage
- Advances in Intelligent and Scientific Computing (AISC)
- Advances in Learning Analytics for Intelligent Cloud-IoT Systems
- Advances in Membrane Processes
- Advances in Nanotechnology and Applications
- Advances in Natural Gas Engineering
- Advances in Petroleum Engineering
- Advances in Pipes and Pipelines
- Advances in Production Engineering
- Advances in Renewable Energy
- Advances in Solar Cell Materials and Storage
- Applied Functional Materials
- Artificial Intelligence and Soft Computing for Industrial Transformation
- Astrobiology Perspectives on Life in the Universe
- Bioprocessing in Food Science
- Computational Intelligence and Biomedical Engineering
- Concise Introductions to AI and Data Science
- Decentralized Systems and Next-Generation Internet
- Diatoms: Biology and Applications
- Digital Convergence in Engineering Systems
- Emerging Trends in Medicinal and Pharmaceutical Chemistry
- Energy and the Environment
- Engineering Systems Design for Sustainable Development
- Fintech in a Sustainable Digital Society
- Handbook of Petroleum Engineering Series
- Industry 5.0 Transformation Applications
- Innovations in Materials and Manufacturing
- Machine Learning in Biomedical Science and Healthcare Informatics
- Materials Degradation and Failure
- Mathematics and Computer Science
- Modern Mathematics in Computer Science
- Next-Generation Computing and Communication Engineering
- Performability Engineering Series
- Power Generation
- Rotating Machinery Fundamentals and Advances
- Studies in Computational Intelligence and Smart Technologies
- Sustainable Computing and Optimization
- Sustainable Energy Engineering
Browse Subject Areas
For Authors
Submit a ProposalRecommender System with Machine Learning and Artificial Intelligence
 | Practical Tools and Applications in Medical, Agricultural and Other Industries Edited by Sachi Nandan Mohanty, Jyotir Moy Chatterjee, Sarika Jain, Ahmed A. Elngar and Priya Gupta Series: Machine Learning in Biomedical Science and Healthcare Informatics Copyright: 2020 | Expected Pub Date:2020/06/16 ISBN: 9781119711575 | Hardcover | 448 pages | 107 illustrations Price: $225 USD  |
One Line Description
This book comprehensively covers all the topics of cutting-edge and emerging recommender systems that provide personalized recommendations of items or services based on past behavior.
Audience
The book will be used by engineers in information technology, artificial intelligence, human-computer interaction, machine learning and analytics specialists, as well as marketers and web managers in industry.
The book will be used by engineers in information technology, artificial intelligence, human-computer interaction, machine learning and analytics specialists, as well as marketers and web managers in industry.
Description
This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. Recommender system methods have been adapted to diverse applications including social networking, movie recommendation, query log mining, news recommendations, and computational advertising.
The 21 chapters are placed in 5 broad sections looking at Introduction to Recommender Systems; Machine Learning-Based Recommender Systems; Content-Based Recommender Systems; Blockchain & IoT-Based Recommender Systems; and Healthcare Recommender Systems. Recommendations in specific domains and contexts, the context of a recommendation can be viewed as important side information that affects the recommendation goals. Different types of context such as temporal data, spatial data, social data, tagging data, and trustworthiness are explored. Various robustness aspects of recommender systems, such as trust-based recommendation system, recommendation system on tourist, medical sciences, and the agricultural field are discussed. In addition, current topics, such as learning to rank, multi-armed bandits, group systems, multicriteria decision support systems, and active learning systems, are introduced together with applications.
Back to Top
This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. Recommender system methods have been adapted to diverse applications including social networking, movie recommendation, query log mining, news recommendations, and computational advertising.
The 21 chapters are placed in 5 broad sections looking at Introduction to Recommender Systems; Machine Learning-Based Recommender Systems; Content-Based Recommender Systems; Blockchain & IoT-Based Recommender Systems; and Healthcare Recommender Systems. Recommendations in specific domains and contexts, the context of a recommendation can be viewed as important side information that affects the recommendation goals. Different types of context such as temporal data, spatial data, social data, tagging data, and trustworthiness are explored. Various robustness aspects of recommender systems, such as trust-based recommendation system, recommendation system on tourist, medical sciences, and the agricultural field are discussed. In addition, current topics, such as learning to rank, multi-armed bandits, group systems, multicriteria decision support systems, and active learning systems, are introduced together with applications.
Back to Top
Author / Editor Details
Sachi Nandan Mohanty received his PhD from IIT Kharagpur, India in 2015 and is now at ICFAI Foundation for Higher Education, Hyderabad, India.
Sachi Nandan Mohanty received his PhD from IIT Kharagpur, India in 2015 and is now at ICFAI Foundation for Higher Education, Hyderabad, India.
Jyotir Moy Chatterjee is working as an Assistant Professor (IT) at Lord Buddha Education Foundation, Kathmandu, Nepal. He has completed M.Tech in Computer Science & Engineering from Kalinga Institute of Industrial Technology, Bhubaneswar, India.
Sarika Jain obtained her PhD in the field of Knowledge Representation in Artificial Intelligence in 2011. She has served in the field of education for over 18 years and is currently in service at the National Institute of Technology, Kurukshetra, India.
Ahmed A. Elngar is the Founder and Head of Scientific Innovation Research Group (SIRG) and Assistant Professor of Computer Science at the Faculty of Computers and Information, Beni-Suef University, Egypt.
Priya Gupta is working as an Assistant Professor in the Department of Computer Science at Maharaja Agrasen College, University of Delhi. Her Doctoral Degree is from BIT (Mesra), Ranchi, India
Back to Top