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Recommender System with Machine Learning and Artificial Intelligence: Practical Tools and Applications in Medical, Agricultural and Other Industries
by Jyotir Moy Chatterjee Sachi Nandan Mohanty Sarika Jain Priya Gupta Ahmed A. ElngarThis 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
by Markus Zanker Dietmar Jannach Alexander Felfernig Gerhard FriedrichIn 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.
Recommender Systems
by Charu C. AggarwalThisbook comprehensively covers the topic of recommender systems, which providepersonalized recommendations of products or services to users based on theirprevious searches or purchases. Recommender system methods have been adapted todiverse applications including query log mining, social networking, newsrecommendations, and computational advertising. This book synthesizes bothfundamental and advanced topics of a research area that has now reachedmaturity. The chapters of this book are organized into three categories: - Algorithms and evaluation: Thesechapters discuss the fundamental algorithms in recommender systems, includingcollaborative filtering methods, content-based methods, knowledge-basedmethods, ensemble-based methods, and evaluation. - Recommendations in specific domains and contexts: the context of a recommendationcan be viewed as important side information that affects the recommendationgoals. Different types of context such as temporal data, spatial data, socialdata, tagging data, and trustworthiness are explored. - Advanced topics and applications: Various robustness aspects of recommender systems, such as shillingsystems, attack models, and their defenses are discussed. Inaddition, recent topics, such as learning to rank, multi-armed bandits, groupsystems, multi-criteria systems, and active learning systems, are introducedtogether with applications. Although this book primarily serves as atextbook, it will also appeal to industrial practitioners and researchers dueto its focus on applications and references. Numerous examples and exerciseshave been provided, and a solution manual is available for instructors.
Recommender Systems
by Gérald Kembellec Ghislaine Chartron Imad SalehAcclaimed by various content platforms (books, music, movies) and auction sites online, recommendation systems are key elements of digital strategies. If development was originally intended for the performance of information systems, the issues are now massively moved on logical optimization of the customer relationship, with the main objective to maximize potential sales. On the transdisciplinary approach, engines and recommender systems brings together contributions linking information science and communications, marketing, sociology, mathematics and computing. It deals with the understanding of the underlying models for recommender systems and describes their historical perspective. It also analyzes their development in the content offerings and assesses their impact on user behavior.
Recommender Systems Handbook
by Lior Rokach Francesco Ricci Bracha ShapiraThis third edition handbook describes in detail the classical methods as well as extensions and novel approaches that were more recently introduced within this field. It consists of five parts: general recommendation techniques, special recommendation techniques, value and impact of recommender systems, human computer interaction, and applications. The first part presents the most popular and fundamental techniques currently used for building recommender systems, such as collaborative filtering, semantic-based methods, recommender systems based on implicit feedback, neural networks and context-aware methods. The second part of this handbook introduces more advanced recommendation techniques, such as session-based recommender systems, adversarial machine learning for recommender systems, group recommendation techniques, reciprocal recommenders systems, natural language techniques for recommender systems and cross-domain approaches to recommender systems. The third part covers a wide perspective to the evaluation of recommender systems with papers on methods for evaluating recommender systems, their value and impact, the multi-stakeholder perspective of recommender systems, the analysis of the fairness, novelty and diversity in recommender systems. The fourth part contains a few chapters on the human computer dimension of recommender systems, with research on the role of explanation, the user personality and how to effectively support individual and group decision with recommender systems. The last part focusses on application in several important areas, such as, food, music, fashion and multimedia recommendation. This informative third edition handbook provides a comprehensive, yet concise and convenient reference source to recommender systems for researchers and advanced-level students focused on computer science and data science. Professionals working in data analytics that are using recommendation and personalization techniques will also find this handbook a useful tool.
Recommender Systems for Learning
by Katrien Verbert Hendrik Drachsler Erik Duval Nikos ManouselisTechnology 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.
Recommender Systems for Location-based Social Networks
by Panagiotis Symeonidis Dimitrios Ntempos Yannis ManolopoulosOnline social networks collect information from users' social contacts and their daily interactions (co-tagging of photos, co-rating of products etc. ) to provide them with recommendations of new products or friends. Lately, technological progressions in mobile devices (i. e. smart phones) enabled the incorporation of geo-location data in the traditional web-based online social networks, bringing the new era of Social and Mobile Web. The goal of this book is to bring together important research in a new family of recommender systems aimed at serving Location-based Social Networks (LBSNs). The chapters introduce a wide variety of recent approaches, from the most basic to the state-of-the-art, for providing recommendations in LBSNs. The book is organized into three parts. Part 1 provides introductory material on recommender systems, online social networks and LBSNs. Part 2 presents a wide variety of recommendation algorithms, ranging from basic to cutting edge, as well as a comparison of the characteristics of these recommender systems. Part 3 provides a step-by-step case study on the technical aspects of deploying and evaluating a real-world LBSN, which provides location, activity and friend recommendations. The material covered in the book is intended for graduate students, teachers, researchers, and practitioners in the areas of web data mining, information retrieval, and machine learning.
Recommender Systems for Medicine and Music (Studies in Computational Intelligence #946)
by Zbigniew W. Ras Alicja Wieczorkowska Shusaku TsumotoMusic recommendation systems are becoming more and more popular. The increasing amount of personal data left by users on social media contributes to more accurate inference of the user’s musical preferences and the same to quality of personalized systems. Health recommendation systems have become indispensable tools in decision making processes in the healthcare sector. Their main objective is to ensure the availability of valuable information at the right time by ensuring information quality, trustworthiness, authentication, and privacy concerns. Medical doctors deal with various kinds of diseases in which the music therapy helps to improve symptoms. Listening to music may improve heart rate, respiratory rate, and blood pressure in people with heart disease. Sound healing therapy uses aspects of music to improve physical and emotional health and well-being. The book presents a variety of approaches useful to create recommendation systems in healthcare, music, and in music therapy.
Recommender Systems for Sustainability and Social Good: First International Workshop, RecSoGood 2024, Bari, Italy, October 18, 2024, Proceedings (Communications in Computer and Information Science #2470)
by Francesco Ricci Ludovico Boratto Elisabeth Lex Allegra De FilippoThis CCIS post conference volume constitutes the proceedings of the First International Workshop on Recommender Systems for Sustainability and Social Good, RecSoGood 2024, in Bari, Italy, in October 2024. The 8 full papers and 6 short papers included in this book were carefully reviewed and selected from 35 submissions. They cover all aspects of Recommender Systems for Sustainable Development Goals; Energy and Carbon Efficiency; and conceptualizations of diversity.
Recommender Systems for Technology Enhanced Learning
by Katrien Verbert Hendrik Drachsler Nikos Manouselis Olga C. SantosAs 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.
Recommender Systems in Fashion and Retail (Lecture Notes in Electrical Engineering #734)
by Nima Dokoohaki Shatha Jaradat Humberto Jesús Corona Pampín Reza ShirvanyThis book includes the proceedings of the second workshop on recommender systems in fashion and retail (2020), and it aims to present a state-of-the-art view of the advancements within the field of recommendation systems with focused application to e-commerce, retail, and fashion by presenting readers with chapters covering contributions from academic as well as industrial researchers active within this emerging new field. Recommender systems are often used to solve different complex problems in this scenario, such as product recommendations, or size and fit recommendations, and social media-influenced recommendations (outfits worn by influencers).
Recommender Systems in Fashion and Retail: Proceedings of the Fourth Workshop at the Recommender Systems Conference (2022) (Lecture Notes in Electrical Engineering #981)
by Humberto Jesús Corona Pampín Reza ShirvanyThis book includes the proceedings of the fourth workshop on recommender systems in fashion and retail (2022), and it aims to present a state-of-the-art view of the advancements within the field of recommendation systems with focused application to e-commerce, retail, and fashion by presenting readers with chapters covering contributions from academic as well as industrial researchers active within this emerging new field. Recommender systems are often used to solve different complex problems in this scenario, such as product recommendations, size and fit recommendations, and social media-influenced recommendations (outfits worn by influencers).
Recommender Systems in Fashion and Retail: Proceedings of the Third Workshop at the Recommender Systems Conference (2021) (Lecture Notes in Electrical Engineering #830)
by Nima Dokoohaki Shatha Jaradat Humberto Jesús Corona Pampín Reza ShirvanyThis book includes the proceedings of the third workshop on recommender systems in fashion and retail (2021), and it aims to present a state-of-the-art view of the advancements within the field of recommendation systems with focused application to e-commerce, retail, and fashion by presenting readers with chapters covering contributions from academic as well as industrial researchers active within this emerging new field. Recommender systems are often used to solve different complex problems in this scenario, such as product recommendations, size and fit recommendations, and social media-influenced recommendations (outfits worn by influencers).
Recommender Systems: A Multi-Disciplinary Approach (Intelligent Systems)
by Monideepa Roy Pushpendu Kar Sujoy DattaRecommender Systems: A Multi-Disciplinary Approach presents a multi-disciplinary approach for the development of recommender systems. It explains different types of pertinent algorithms with their comparative analysis and their role for different applications. This book explains the big data behind recommender systems, the marketing benefits, how to make good decision support systems, the role of machine learning and artificial networks, and the statistical models with two case studies. It shows how to design attack resistant and trust-centric recommender systems for applications dealing with sensitive data. Features of this book: Identifies and describes recommender systems for practical uses Describes how to design, train, and evaluate a recommendation algorithm Explains migration from a recommendation model to a live system with users Describes utilization of the data collected from a recommender system to understand the user preferences Addresses the security aspects and ways to deal with possible attacks to build a robust system This book is aimed at researchers and graduate students in computer science, electronics and communication engineering, mathematical science, and data science.
Recommender Systems: Algorithms and Applications
by Sachi Nandan Mohanty P. Pavan Kumar S. Vairachilai Sirisha PotluriRecommender 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.
Recommender Systems: Algorithms and their Applications (Transactions on Computer Systems and Networks)
by Monideepa Roy Pushpendu Kar Sujoy DattaThe book includes a thorough examination of the many types of algorithms for recommender systems, as well as a comparative analysis of them. It addresses the problem of dealing with the large amounts of data generated by the recommender system. The book also includes two case studies on recommender system applications in healthcare monitoring and military surveillance. It demonstrates how to create attack-resistant and trust-centric recommender systems for sensitive data applications. This book provides a solid foundation for designing recommender systems for use in healthcare and defense.
Recommender Systems: Frontiers and Practices
by Xing Xie Tun Lu Tao Wu Dongsheng Li Le Zhang Jianxun Lian Kan RenThis book starts from the classic recommendation algorithms, introduces readers to the basic principles and main concepts of the traditional algorithms, and analyzes their advantages and limitations. Then, it addresses the fundamentals of deep learning, focusing on the deep-learning-based technology used, and analyzes problems arising in the theory and practice of recommender systems, helping readers gain a deeper understanding of the cutting-edge technology used in these systems. Lastly, it shares practical experience with Microsoft 's open source project Microsoft Recommenders. Readers can learn the design principles of recommendation algorithms using the source code provided in this book, allowing them to quickly build accurate and efficient recommender systems from scratch.
Reconceptualising Learning in the Digital Age: The [un]democratising Potential Of Moocs (SpringerBriefs in Education)
by Allison Littlejohn Nina HoodThis book situates Massive Open Online Courses and open learning within a broader educational, economic and social context. It raises questions regarding whether Massive Open Online Courses effectively address demands to open up access to education by triggering a new education order, or merely represent reactionary and unimaginative responses to those demands. It offers a fresh perspective on how we conceptualise learners and learning, teachers and teaching, accreditation and quality, and how these dimensions fit within the emerging landscape of new forms of open learning.
Reconceptualizing Libraries: Perspectives from the Information and Learning Sciences
by Victor R. Lee Abigail L. PhillipsReconceptualizing Libraries brings together cases and models developed by experts in the information and learning sciences to identify the potential for libraries to adapt and transform in the wake of new technologies for connected learning and discovery. Chapter authors explore the ways that the increased interest in the design research methods, digital media emphases, and technological infrastructure of the learning sciences can foster new collaborations and formats for education within physical library spaces. Models and case studies from a variety of library contexts demonstrate how library professionals can act as change agents and design partners and how patrons can engage with these evolving experiences. This is a timely and innovative volume for understanding how physical libraries can incorporate and thrive as educational resources using new developments in technology and in the learning sciences.
Reconceptualizing the Digital Humanities in Asia: New Representations of Art, History and Culture (Digital Culture and Humanities #2)
by Kaby Wing-Sze KungThis book examines new forms of representation that have changed our perception and interpretation of the humanities in an Asian, and digital, context. In analyzing written and visual texts, such as the use of digital technology and animation in different works of art originating from Asia, the authors demonstrate how literature, history, and culture are being redefined in spatialized relations amid the trend of digitization. Research studies on Asian animation are in short supply, and so this volume provides new and much needed insights into how art, literature, history, and culture can be presented in innovative ways in the Asian digital world. The first section of this volume focuses on the new conceptualization of the digital humanities in art and film studies, looking at the integration of digital technologies in museum narration and cinematic production. The second section of the volume addresses the importance of framing these discussions within the context of gender issues in the digital world, discussing how women are represented in different forms of social media. The third and final section of the book explores the digital world’s impacts on people’s lives through different forms of digital media, from the electromagnetic unconscious to digital storytelling and digital online games. This book presents a novel contribution to the burgeoning field of the digital humanities by informing new forms of representation and interpretations, and demonstrating how digitization can influence and change cultural practices in Asia, and globally. It will be of interest to students and scholars interested in digitization from the full spectrum of humanities disciplines, including art, literature, film, music, visual culture, media, and animation, gaming, and Internet culture."This is a well-written book, and I enjoyed reading it. The first impression of the book is that it is very innovative - a down-to-the-earth academic volume that discusses digital culture."- Professor Anthony Fung, Professor, Director, School of Journalism and Communication, The Chinese University of Hong Kong "This book has contributed to the existing field of humanities by informing new forms of representation and interpretations, and how digitization may change cultural practices. There is comprehensive information on how the humanities in the digital age can be applied to a wide range of subjects including art, literature, film, pop music, music videos, television, animation, games, and internet culture."- Dr Samuel Chu, Associate Professor, The Faculty of Education, The University of Hong Kong
Reconciliation of Geometry and Perception in Radiation Physics
by Benoit Beckers Pierre BeckersReconciliation of Geometry and Perception in Radiation Physics approaches the topic of projective geometry as it applies to radiation physics and attempts to negate its negative reputation. With an original outlook and transversal approach, the book emphasizes common geometric properties and their potential transposition between domains. After defining both radiation and geometric properties, authors Benoit and Pierre Beckers explain the necessity of reconciling geometry and perception in fields like architectural and urban physics, which are notable for the regularity of their forms and the complexity of their interactions.
Reconfigurable Cellular Neural Networks and Their Applications (SpringerBriefs in Applied Sciences and Technology)
by Müştak E. Yalçın Tuba Ayhan Ramazan YeniçeriThis book explores how neural networks can be designed to analyze sensory data in a way that mimics natural systems. It introduces readers to the cellular neural network (CNN) and formulates it to match the behavior of the Wilson–Cowan model. In turn, two properties that are vital in nature are added to the CNN to help it more accurately deliver mimetic behavior: randomness of connection, and the presence of different dynamics (excitatory and inhibitory) within the same network. It uses an ID matrix to determine the location of excitatory and inhibitory neurons, and to reconfigure the network to optimize its topology. The book demonstrates that reconfiguring a single-layer CNN is an easier and more flexible solution than the procedure required in a multilayer CNN, in which excitatory and inhibitory neurons are separate, and that the key CNN criteria of a spatially invariant template and local coupling are fulfilled. In closing, the application of the authors’ neuron population model as a feature extractor is exemplified using odor and electroencephalogram classification.
Reconfigurable Computing
by Michael Hübner João M. CardosoAs the complexity of modern embedded systems increases, it becomes less practical to design monolithic processing platforms. As a result, reconfigurable computing is being adopted widely for more flexible design. Reconfigurable Computers offer the spatial parallelism and fine-grained customizability of application-specific circuits with the postfabrication programmability of software. To make the most of this unique combination of performance and flexibility, designers need to be aware of both hardware and software issues. FPGA users must think not only about the gates needed to perform a computation but also about the software flow that supports the design process. The goal of this book is to help designers become comfortable with these issues, and thus be able to exploit the vast opportunities possible with reconfigurable logic.
Reconfigurable Computing Systems Engineering: Virtualization of Computing Architecture
by Lev KirischianReconfigurable Computing Systems Engineering: Virtualization of Computing Architecture describes the organization of reconfigurable computing system (RCS) architecture and discusses the pros and cons of different RCS architecture implementations. Providing a solid understanding of RCS technology and where it’s most effective, this book: Details the architecture organization of RCS platforms for application-specific workloads Covers the process of the architectural synthesis of hardware components for system-on-chip (SoC) for the RCS Explores the virtualization of RCS architecture from the system and on-chip levels Presents methodologies for RCS architecture run-time integration according to mode of operation and rapid adaptation to changes of multi-parametric constraints Includes illustrative examples, case studies, homework problems, and references to important literature A solutions manual is available with qualifying course adoption. Reconfigurable Computing Systems Engineering: Virtualization of Computing Architecture offers a complete road map to the synthesis of RCS architecture, exposing hardware design engineers, system architects, and students specializing in designing FPGA-based embedded systems to novel concepts in RCS architecture organization and virtualization.
Reconfigurable Cryptographic Processor
by Bo Wang Leibo Liu Shaojun WeiThis book focuses on the design methods for reconfigurable computing processors for cryptographic algorithms. It covers the dynamic reconfiguration analysis of cryptographic algorithms, hardware architecture design, and compilation techniques for reconfigurable cryptographic processors, and also presents a case study of implementing the reconfigurable cryptographic processor “Anole” designed by the authors’ team. Moreover, it features discussions on countermeasures against physical attacks utilizing partially and dynamically reconfigurable array architecture to enhance security, as well as the latest trends for reconfigurable cryptographic processors. This book is intended for research scientists, graduate students, and engineers in electronic science and technology, cryptography, network and information security, as well as computer science and technology.