Artificial Intelligence and Data Science in Recommendation System: Current Trends, Technologies and Applications - 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 Artificial Intelligence and Data Science in Recommendation System: Current Trends, Technologies and Applications write by Abhishek Majumder. This book was released on 2023-08-16. Artificial Intelligence and Data Science in Recommendation System: Current Trends, Technologies and Applications available in PDF, EPUB and Kindle. Artificial Intelligence and Data Science in Recommendation System: Current Trends, Technologies and Applications captures the state of the art in usage of artificial intelligence in different types of recommendation systems and predictive analysis. The book provides guidelines and case studies for application of artificial intelligence in recommendation from expert researchers and practitioners. A detailed analysis of the relevant theoretical and practical aspects, current trends and future directions is presented. The book highlights many use cases for recommendation systems: · Basic application of machine learning and deep learning in recommendation process and the evaluation metrics · Machine learning techniques for text mining and spam email filtering considering the perspective of Industry 4.0 · Tensor factorization in different types of recommendation system · Ranking framework and topic modeling to recommend author specialization based on content. · Movie recommendation systems · Point of interest recommendations · Mobile tourism recommendation systems for visually disabled persons · Automation of fashion retail outlets · Human resource management (employee assessment and interview screening) This reference is essential reading for students, faculty members, researchers and industry professionals seeking insight into the working and design of recommendation systems.
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: Advanced Developments
Recommender Systems: Advanced Developments - 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: Advanced Developments write by Jie Lu. This book was released on 2020-08-04. Recommender Systems: Advanced Developments available in PDF, EPUB and Kindle. Recommender systems provide users (businesses or individuals) with personalized online recommendations of products or information, to address the problem of information overload and improve personalized services. Recent successful applications of recommender systems are providing solutions to transform online services for e-government, e-business, e-commerce, e-shopping, e-library, e-learning, e-tourism, and more.This unique compendium not only describes theoretical research but also reports on new application developments, prototypes, and real-world case studies of recommender systems. The comprehensive volume provides readers with a timely snapshot of how new recommendation methods and algorithms can overcome challenging issues. Furthermore, the monograph systematically presents three dimensions of recommender systems — basic recommender system concepts, advanced recommender system methods, and real-world recommender system applications.By providing state-of-the-art knowledge, this excellent reference text will immensely benefit researchers, managers, and professionals in business, government, and education to understand the concepts, methods, algorithms and application developments in recommender systems.
Recommender Systems Handbook
Recommender Systems Handbook - 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 Handbook write by Francesco Ricci. This book was released on 2010-10-21. Recommender Systems Handbook available in PDF, EPUB and Kindle. The explosive growth of e-commerce and online environments has made the issue of information search and selection increasingly serious; users are overloaded by options to consider and they may not have the time or knowledge to personally evaluate these options. Recommender systems have proven to be a valuable way for online users to cope with the information overload and have become one of the most powerful and popular tools in electronic commerce. Correspondingly, various techniques for recommendation generation have been proposed. During the last decade, many of them have also been successfully deployed in commercial environments. Recommender Systems Handbook, an edited volume, 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. Theoreticians and practitioners from these fields continually seek techniques for more efficient, cost-effective and accurate recommender systems. This handbook aims to impose a degree of order on this diversity, by presenting a coherent and unified repository of recommender systems’ major concepts, theories, methodologies, trends, challenges and applications. Extensive artificial applications, a variety of real-world applications, and detailed case studies are included. Recommender Systems Handbook illustrates how this technology can support the user in decision-making, planning and purchasing processes. It works for well known corporations such as Amazon, Google, Microsoft and AT&T. This handbook is suitable for researchers and advanced-level students in computer science as a reference.
Recommender Systems for Technology Enhanced Learning
Recommender Systems for Technology Enhanced 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 Technology Enhanced Learning write by Nikos Manouselis. This book was released on 2014-04-12. Recommender Systems for Technology Enhanced Learning available in PDF, EPUB and Kindle. As an area, Technology Enhanced Learning (TEL) aims to design, develop and test socio-technical innovations that will support and enhance learning practices of individuals and organizations. Information retrieval is a pivotal activity in TEL and the deployment of recommender systems has attracted increased interest during the past years. Recommendation methods, techniques and systems open an interesting new approach to facilitate and support learning and teaching. The goal is to develop, deploy and evaluate systems that provide learners and teachers with meaningful guidance in order to help identify suitable learning resources from a potentially overwhelming variety of choices. Contributions address the following topics: i) user and item data that can be used to support learning recommendation systems and scenarios, ii) innovative methods and techniques for recommendation purposes in educational settings and iii) examples of educational platforms and tools where recommendations are incorporated.
