Recommender Systems for Learning - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Recommender Systems for Learning write by Nikos Manouselis. This book was released on 2012-08-28. Recommender Systems for Learning available in PDF, EPUB and Kindle. Technology enhanced learning (TEL) aims to design, develop and test sociotechnical innovations that will support and enhance learning practices of both individuals and organisations. It is therefore an application domain that generally covers technologies that support all forms of teaching and learning activities. Since information retrieval (in terms of searching for relevant learning resources to support teachers or learners) is a pivotal activity in TEL, the deployment of recommender systems has attracted increased interest. This brief attempts to provide an introduction to recommender systems for TEL settings, as well as to highlight their particularities compared to recommender systems for other application domains.
Educational Recommender Systems and Technologies
Educational Recommender Systems and Technologies - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Educational Recommender Systems and Technologies write by Olga C. Santos. This book was released on 2012. Educational Recommender Systems and Technologies available in PDF, EPUB and Kindle. "This book aims to provide a comprehensive review of state-of-the-art practices for educational recommender systems, as well as the challenges to achieve their actual deployment"--Provided by publisher.
Recommender System with Machine Learning and Artificial Intelligence
Recommender System with Machine Learning and Artificial Intelligence - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Recommender System with Machine Learning and Artificial Intelligence write by Sachi Nandan Mohanty. This book was released on 2020-07-08. Recommender System with Machine Learning and Artificial Intelligence available in PDF, EPUB and Kindle. This book is a multi-disciplinary effort that involves world-wide experts from diverse fields, such as artificial intelligence, human computer interaction, information technology, data mining, statistics, adaptive user interfaces, decision support systems, marketing, and consumer behavior. It comprehensively covers the topic of recommender systems, which provide personalized recommendations of items or services to the new users based on their past behavior. Recommender system methods have been adapted to diverse applications including social networking, movie recommendation, query log mining, news recommendations, and computational advertising. This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. Recommendations in agricultural or healthcare 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. This book illustrates how this technology can support the user in decision-making, planning and purchasing processes in agricultural & healthcare sectors.
Recommender Systems
Recommender Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Recommender Systems write by Charu C. Aggarwal. This book was released on 2016-03-28. Recommender Systems available in PDF, EPUB and Kindle. This book comprehensively covers the topic of recommender systems, which provide personalized recommendations of products or services to users based on their previous searches or purchases. Recommender system methods have been adapted to diverse applications including query log mining, social networking, news recommendations, and computational advertising. This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. The chapters of this book are organized into three categories: Algorithms and evaluation: These chapters 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: 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. Advanced topics and applications: Various robustness aspects of recommender systems, such as shilling systems, attack models, and their defenses are discussed. In addition, recent topics, such as learning to rank, multi-armed bandits, group systems, multi-criteria systems, and active learning systems, are introduced together with applications. Although this book primarily serves as a textbook, it will also appeal to industrial practitioners and researchers due to its focus on applications and references. Numerous examples and exercises have been provided, and a solution manual is available for instructors.
Machine Learning Approaches for Improvising Modern Learning Systems
Machine Learning Approaches for Improvising Modern Learning Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Machine Learning Approaches for Improvising Modern Learning Systems write by Gulzar, Zameer. This book was released on 2021-05-14. Machine Learning Approaches for Improvising Modern Learning Systems available in PDF, EPUB and Kindle. Technology is currently playing a vital role in revolutionizing education systems and progressing academia into the digital age. Technological methods including data mining and machine learning are assisting with the discovery of new techniques for improving learning environments in regions across the world. As the educational landscape continues to rapidly transform, researchers and administrators need to stay up to date on the latest advancements in order to elevate the quality of teaching in their specific institutions. Machine Learning Approaches for Improvising Modern Learning Systems provides emerging research exploring the theoretical and practical aspects of technological enhancements in educational environments and the popularization of contemporary learning methods in developing countries. Featuring coverage on a broad range of topics such as game-based learning, intelligent tutoring systems, and course modelling, this book is ideally designed for researchers, scholars, administrators, policymakers, students, practitioners, and educators seeking current research on the digital transformation of educational institutions.
