RSTools 2020: Recommender System with Machine Learning and Artificial Intelligence: Practical Tools and Applications in Medical and Agricultural Domains |
Submission link | https://easychair.org/conferences/?conf=rstools2020 |
Poster | download |
The edited book "Recommender System with Machine Learning and Artificial Intelligence: Practical Tools and Applications in Medical and Agricultural Domains" is intended to discuss the recommender systems, which aid to personalize the recommendations of items/services to the users based on their past behavior. It will also help students, academicians, researchers and industry experts working on Recommender System methods that have been adapted to diverse applications including social networking, movie recommendation, query log mining, news recommendations, and computational advertising. Therefore, the major objective of this book is providing a Recommender system for presenting Machine Learning and Artificial Intelligence techniques employed in medical and Agricultural Domains. Finally, this book synthesizes both fundamental and advanced topics of research areas that have reached maturity. The chapters of this proceeding are organized into three parts:
Algorithms and quantitative approach: The chapters in this part will discuss the fundamental algorithms in recommender systems, including collaborative filtering methods, content-based methods, knowledge-based methods, ensemble-based methods, and evaluation.
Recommendations in specific domains and contexts: In this part, the chapters will give the context of a recommendation which can be viewed as important side information that affects the recommendation goals. Also, different types of context such as temporal data, spatial data, social data, tagging data, and trustworthiness are explored.
Applications: The chapters in the final part will discuss various robustness aspects of recommender systems, such as Trust-based recommendation system, Recommendation system on Tourist, Medical Sciences, and Agriculture field, are discussed.
In addition, current topics, such as learning to rank, multi-armed bandits, group systems, multi-criteria decision support systems, and active learning systems, are introduced together with applications.
Submission Guidelines
All submitted chapters must be original and not simultaneously under consideration as a manuscript in any journal or conference or another book.
The submission Web page for RSTools 2020 is https://easychair.org/conferences/?conf=rstools2020
Abstract submission deadline: 10.10.2019
Abstract Acceptance Deadline:30.10.2019
Full Chapter Submission: 25.11.2019
Review Notification: 05.01.2020
Revised version submission Deadline:15.01.2020
Final Decision Notification:30.01.2020
List of Topics
- Quantitative Approach to Recommender Systems
- Recommender in Medical Domain
- Recommender in Agriculture Domain
- Computer Science
- Artificial Intelligence
- Machine Learning
Editors
- Dr. Sachi Nandan Mohanty
- Dr. Ahmed A. Elngar
- Dr. Priya Gupta
- Dr. Sarika Jain
- Prof. Jyotir Moy Chatterjee
Publication
RSTools 2020 proceedings will be published by Scrivener Publishing LLC (Wiley & Sons,USA)
Contact
All questions about submissions should be emailed to sachinandan09@gmail.com or jyotirchatterjee@gmail.com