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Educational Recommender Systems And Technologies
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Book Synopsis Educational Recommender Systems and Technologies by : Olga C. Santos
Download or read book Educational Recommender Systems and Technologies written by Olga C. Santos and published by . This book was released on 2012 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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.
Book Synopsis Recommender Systems for Learning by : Nikos Manouselis
Download or read book Recommender Systems for Learning written by Nikos Manouselis and published by Springer. This book was released on 2012-08-28 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Educational Recommender Systems and Technologies: Practices and Challenges by : Santos, Olga C.
Download or read book Educational Recommender Systems and Technologies: Practices and Challenges written by Santos, Olga C. and published by IGI Global. This book was released on 2011-12-31 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recommender systems have shown to be successful in many domains where information overload exists. This success has motivated research on how to deploy recommender systems in educational scenarios to facilitate access to a wide spectrum of information. Tackling open issues in their deployment is gaining importance as lifelong learning becomes a necessity of the current knowledge-based society. Although Educational Recommender Systems (ERS) share the same key objectives as recommenders for e-commerce applications, there are some particularities that should be considered before directly applying existing solutions from those applications. Educational Recommender Systems and Technologies: Practices and Challenges aims to provide a comprehensive review of state-of-the-art practices for ERS, as well as the challenges to achieve their actual deployment. Discussing such topics as the state-of-the-art of ERS, methodologies to develop ERS, and architectures to support the recommendation process, this book covers researchers interested in recommendation strategies for educational scenarios and in evaluating the impact of recommendations in learning, as well as academics and practitioners in the area of technology enhanced learning.
Book Synopsis Recommender System with Machine Learning and Artificial Intelligence by : Sachi Nandan Mohanty
Download or read book Recommender System with Machine Learning and Artificial Intelligence written by Sachi Nandan Mohanty and published by John Wiley & Sons. This book was released on 2020-07-08 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Recommender Systems by : P. Pavan Kumar
Download or read book Recommender Systems written by P. Pavan Kumar and published by CRC Press. This book was released on 2021-06-01 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recommender systems use information filtering to predict user preferences. They are becoming a vital part of e-business and are used in a wide variety of industries, ranging from entertainment and social networking to information technology, tourism, education, agriculture, healthcare, manufacturing, and retail. Recommender Systems: Algorithms and Applications dives into the theoretical underpinnings of these systems and looks at how this theory is applied and implemented in actual systems. The book examines several classes of recommendation algorithms, including Machine learning algorithms Community detection algorithms Filtering algorithms Various efficient and robust product recommender systems using machine learning algorithms are helpful in filtering and exploring unseen data by users for better prediction and extrapolation of decisions. These are providing a wider range of solutions to such challenges as imbalanced data set problems, cold-start problems, and long tail problems. This book also looks at fundamental ontological positions that form the foundations of recommender systems and explain why certain recommendations are predicted over others. Techniques and approaches for developing recommender systems are also investigated. These can help with implementing algorithms as systems and include A latent-factor technique for model-based filtering systems Collaborative filtering approaches Content-based approaches Finally, this book examines actual systems for social networking, recommending consumer products, and predicting risk in software engineering projects.
Book Synopsis Recommender Systems for Technology Enhanced Learning by : Nikos Manouselis
Download or read book Recommender Systems for Technology Enhanced Learning written by Nikos Manouselis and published by Springer Science & Business Media. This book was released on 2014-04-12 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Machine Learning Approaches for Improvising Modern Learning Systems by : Zameer Gulzar
Download or read book Machine Learning Approaches for Improvising Modern Learning Systems written by Zameer Gulzar and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book explores the theoretical and practical aspects of technological enhancements in educational environments and the popularization of contemporary learning methods in developing countries"--
Book Synopsis Recommender Systems Handbook by : Francesco Ricci
Download or read book Recommender Systems Handbook written by Francesco Ricci and published by Springer. This book was released on 2015-11-17 with total page 1008 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition of a well-received text, with 20 new chapters, presents a coherent and unified repository of recommender systems’ major concepts, theories, methodologies, trends, and challenges. A variety of real-world applications and detailed case studies are included. In addition to wholesale revision of the existing chapters, this edition includes new topics including: decision making and recommender systems, reciprocal recommender systems, recommender systems in social networks, mobile recommender systems, explanations for recommender systems, music recommender systems, cross-domain recommendations, privacy in recommender systems, and semantic-based recommender systems. This multi-disciplinary handbook involves world-wide experts from diverse fields such as artificial intelligence, human-computer interaction, information retrieval, data mining, mathematics, statistics, adaptive user interfaces, decision support systems, psychology, marketing, and consumer behavior. Theoreticians and practitioners from these fields will find this reference to be an invaluable source of ideas, methods and techniques for developing more efficient, cost-effective and accurate recommender systems.
Book Synopsis Digital Innovations for Customer Engagement, Management, and Organizational Improvement by : Sandhu, Kamaljeet
Download or read book Digital Innovations for Customer Engagement, Management, and Organizational Improvement written by Sandhu, Kamaljeet and published by IGI Global. This book was released on 2020-06-12 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past several years, digital technologies have reestablished the ways in which corporations operate. On one hand, technology has allowed companies to build a stronger knowledge of its customer base, contributing to better consumer engagement strategies. On the other hand, these technologies have also integrated into the management and daily operations of companies, resulting in increased performance and organizational improvement. Remaining up to date with the implementation of these cutting-edge technologies is key to a company’s continued success. Digital Innovations for Customer Engagement, Management, and Organizational Improvement is an essential reference source that discusses and strategizes the latest technologies and innovations and their integration, implementation, and use in businesses, as well as lifelong learning strategies in a digital environment. Featuring research on topics such as consumer engagement, e-commerce, and learning management systems, this book is ideally designed for managers, business executives, marketers, consumer analysts, IT consultants, industry professionals, academicians, researchers, and students.
Book Synopsis Recommender Systems by : Charu C. Aggarwal
Download or read book Recommender Systems written by Charu C. Aggarwal and published by Springer. This book was released on 2016-03-28 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Recommender Systems: Advanced Developments by : Jie Lu
Download or read book Recommender Systems: Advanced Developments written by Jie Lu and published by World Scientific. This book was released on 2020-08-04 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Developments Of Artificial Intelligence Technologies In Computation And Robotics - Proceedings Of The 14th International Flins Conference (Flins 2020) by : Zhong Li
Download or read book Developments Of Artificial Intelligence Technologies In Computation And Robotics - Proceedings Of The 14th International Flins Conference (Flins 2020) written by Zhong Li and published by World Scientific. This book was released on 2020-08-04 with total page 1588 pages. Available in PDF, EPUB and Kindle. Book excerpt: FLINS, an acronym introduced in 1994 and originally for Fuzzy Logic and Intelligent Technologies in Nuclear Science, is now extended into a well-established international research forum to advance the foundations and applications of computational intelligence for applied research in general and for complex engineering and decision support systems.The principal mission of FLINS is bridging the gap between machine intelligence and real complex systems via joint research between universities and international research institutions, encouraging interdisciplinary research and bringing multidiscipline researchers together.FLINS 2020 is the fourteenth in a series of conferences on computational intelligence systems.
Book Synopsis Methodologies and Intelligent Systems for Technology Enhanced Learning, 10th International Conference by : Pierpaolo Vittorini
Download or read book Methodologies and Intelligent Systems for Technology Enhanced Learning, 10th International Conference written by Pierpaolo Vittorini and published by Springer Nature. This book was released on 2020-07-27 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book intends to bring together researchers and developers from industry, the education field, and the academic world to report on the latest scientific research, technical advances, and methodologies. The 10th International Conference in Methodologies and Intelligent Systems for Technology Enhanced Learning is hosted by the University of L’Aquila and is going to be held in L’Aquila (Italy). Initially planned on the 17th to the 19th of June 2020, it was postponed to the 7th to the 9th of October 2020, due to the COVID-19 outbreak. The 10th edition of this conference and its related workshops expand the topics of the evidence-based TEL workshops series in order to provide an open forum for discussing intelligent systems for TEL, their roots in novel learning theories, empirical methodologies for their design or evaluation, stand-alone solutions, or web-based ones. This bridge has been realized also thanks to the sponsor of this edition of MIS4TEL: the Armundia Group https://www.armundia.com, the support from national associations (AEPIA, APPIA, CINI, and EurAI), and organizers (UNIVAQ, UNIROMA1, UNIBZ, UCV, UFSC, USAL, AIR institute, UNC, and UNIBA)
Book Synopsis Building Recommender Systems with Machine Learning and AI. by : Frank Kane
Download or read book Building Recommender Systems with Machine Learning and AI. written by Frank Kane and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Automated recommendations are everywhere: Netflix, Amazon, YouTube, and more. Recommender systems learn about your unique interests and show the products or content they think you'll like best. Discover how to build your own recommender systems from one of the pioneers in the field. Frank Kane spent over nine years at Amazon, where he led the development of many of the company's personalized product recommendation technologies. In this course, he covers recommendation algorithms based on neighborhood-based collaborative filtering and more modern techniques, including matrix factorization and even deep learning with artificial neural networks. Along the way, you can learn from Frank's extensive industry experience and understand the real-world challenges of applying these algorithms at a large scale with real-world data. You can also go hands-on, developing your own framework to test algorithms and building your own neural networks using technologies like Amazon DSSTNE, AWS SageMaker, and TensorFlow.
Book Synopsis Learning Technology for Education Challenges by : Lorna Uden
Download or read book Learning Technology for Education Challenges written by Lorna Uden and published by Springer. This book was released on 2017-08-07 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 6th International Workshop on Learning Technology for Education in Cloud, LTEC 2017, held in Beijing, China, in August 2017. The 16 revised full papers presented were carefully reviewed and selected from 37 submissions. The papers are organized in topical sections on Learning Technologies; Learning Tools and Environment; Online Learning and MOOC; Problem Solving and Knowledge Transfer.
Book Synopsis Recommender Systems for Learning by : Nikos Manouselis
Download or read book Recommender Systems for Learning written by Nikos Manouselis and published by Springer Science & Business Media. This book was released on 2012-08-28 with total page 85 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Recommender Systems by : Dietmar Jannach
Download or read book Recommender Systems written by Dietmar Jannach and published by Cambridge University Press. This book was released on 2010-09-30 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this age of information overload, people use a variety of strategies to make choices about what to buy, how to spend their leisure time, and even whom to date. Recommender systems automate some of these strategies with the goal of providing affordable, personal, and high-quality recommendations. This book offers an overview of approaches to developing state-of-the-art recommender systems. The authors present current algorithmic approaches for generating personalized buying proposals, such as collaborative and content-based filtering, as well as more interactive and knowledge-based approaches. They also discuss how to measure the effectiveness of recommender systems and illustrate the methods with practical case studies. The final chapters cover emerging topics such as recommender systems in the social web and consumer buying behavior theory. Suitable for computer science researchers and students interested in getting an overview of the field, this book will also be useful for professionals looking for the right technology to build real-world recommender systems.
