Download or read book Recommender Systems for Medicine and Music written by Zbigniew W. Ras and published by Springer Nature. This book was released on 2021-04-07 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Music 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.

Download or read book From the ear to the brain new data analytics techniques for a better understanding of human hearing written by Alessia Paglialonga and published by Frontiers Media SA. This book was released on 2023-06-23 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Mathematical Modeling and Simulation of Systems written by Volodymyr Kazymyr and published by Springer Nature. This book was released on with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Information Technology for Education Science and Technics written by Emil Faure and published by Springer Nature. This book was released on 2023-06-17 with total page 772 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers selected high-quality full-text papers presented at the VI International Scientific and Practical Conference on Information Technology for Education, Science and Technics (ITEST 2022). The book deals with issues related to mathematical and computer modeling of physical, chemical, and economic processes, with information security, as well as the use of information and communication technology in scientific research, automation of technological processes, and management of complex systems. In this book, the authors explore various aspects of the development of information technology and systems and its application in education, science, engineering, economics, and management. A part of the book is devoted to the application of information and communication technology in higher education, in particular, the creation and implementation of scientific and educational resources in higher education institutions as part of the process of education digital transformation.

Download or read book Encyclopedia of Data Science and Machine Learning written by Wang, John and published by IGI Global. This book was released on 2023-01-20 with total page 3296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.

Download or read book Computational Intelligence for Machine Learning and Healthcare Informatics written by Rajshree Srivastava and published by Walter de Gruyter GmbH & Co KG. This book was released on 2020-06-22 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. It is intended to provide a unique compendium of current and emerging machine learning paradigms for healthcare informatics, reflecting the diversity, complexity, and depth and breadth of this multi-disciplinary area.

Download or read book Foundations of Intelligent Systems written by Michelangelo Ceci and published by Springer Nature. This book was released on 2022-09-26 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 26th International Symposium on Foundations of Intelligent Systems, ISMIS 2022, held in Cosenza, Italy, in October 2022. The 31 regular papers, 11 short papers and 4 industrial papers presented in this volume were carefully reviewed and selected from 71 submissions. They were organized in topical sections as follows: Social Media and Recommendation; Natural Language Processing; Explainability; Intelligent Systems; Classification and Clustering; Complex Data; Medical Applications; Industrial Applications.

Download or read book 7th International Conference on Advancements of Medicine and Health Care through Technology written by Simona Vlad and published by Springer Nature. This book was released on 2022-01-01 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers the proceedings of the 7th International Conference on Advancements of Medicine and Health Care through Technology, held virtually on 13 – 15 October 2020, from Cluj-Napoca, Romania. It reports on both theoretical and practical developments fostering the use of cutting-edge technology in clinical settings, telemedicine, and biological research. Chapters mainly deal with medical devices, measurements and instrumentation, medical imaging and biological signal processing and health care information systems. Further topics include modeling, simulation and biomechanics, as well as innovative (bio-)materials for biomedical applications. The conference, as well as the realization of this book, was supported by the Romanian Society for Medical Engineering and Biological Technology.

Download or read book Machine Learning and Knowledge Discovery in Databases written by Massih-Reza Amini and published by Springer Nature. This book was released on 2023-03-16 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: The multi-volume set LNAI 13713 until 13718 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2022, which took place in Grenoble, France, in September 2022. The 236 full papers presented in these proceedings were carefully reviewed and selected from a total of 1060 submissions. In addition, the proceedings include 17 Demo Track contributions. The volumes are organized in topical sections as follows: Part I: Clustering and dimensionality reduction; anomaly detection; interpretability and explainability; ranking and recommender systems; transfer and multitask learning; Part II: Networks and graphs; knowledge graphs; social network analysis; graph neural networks; natural language processing and text mining; conversational systems; Part III: Deep learning; robust and adversarial machine learning; generative models; computer vision; meta-learning, neural architecture search; Part IV: Reinforcement learning; multi-agent reinforcement learning; bandits and online learning; active and semi-supervised learning; private and federated learning; Part V: Supervised learning; probabilistic inference; optimal transport; optimization; quantum, hardware; sustainability; Part VI: Time series; financial machine learning; applications; applications: transportation; demo track.

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.

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 2020-06-09 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.

Download or read book Practical Recommender Systems written by Kim Falk and published by Simon and Schuster. This book was released on 2019-01-18 with total page 743 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Online recommender systems help users find movies, jobs, restaurants-even romance! There's an art in combining statistics, demographics, and query terms to achieve results that will delight them. Learn to build a recommender system the right way: it can make or break your application! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Recommender systems are everywhere, helping you find everything from movies to jobs, restaurants to hospitals, even romance. Using behavioral and demographic data, these systems make predictions about what users will be most interested in at a particular time, resulting in high-quality, ordered, personalized suggestions. Recommender systems are practically a necessity for keeping your site content current, useful, and interesting to your visitors. About the Book Practical Recommender Systems explains how recommender systems work and shows how to create and apply them for your site. After covering the basics, you'll see how to collect user data and produce personalized recommendations. You'll learn how to use the most popular recommendation algorithms and see examples of them in action on sites like Amazon and Netflix. Finally, the book covers scaling problems and other issues you'll encounter as your site grows. What's inside How to collect and understand user behavior Collaborative and content-based filtering Machine learning algorithms Real-world examples in Python About the Reader Readers need intermediate programming and database skills. About the Author Kim Falk is an experienced data scientist who works daily with machine learning and recommender systems. Table of Contents PART 1 - GETTING READY FOR RECOMMENDER SYSTEMS What is a recommender? User behavior and how to collect it Monitoring the system Ratings and how to calculate them Non-personalized recommendations The user (and content) who came in from the cold PART 2 - RECOMMENDER ALGORITHMS Finding similarities among users and among content Collaborative filtering in the neighborhood Evaluating and testing your recommender Content-based filtering Finding hidden genres with matrix factorization Taking the best of all algorithms: implementing hybrid recommenders Ranking and learning to rank Future of recommender systems

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.

Download or read book Machine Learning for Health Informatics written by Andreas Holzinger and published by Springer. This book was released on 2016-12-09 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning (ML) is the fastest growing field in computer science, and Health Informatics (HI) is amongst the greatest application challenges, providing future benefits in improved medical diagnoses, disease analyses, and pharmaceutical development. However, successful ML for HI needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. Tackling complex challenges needs both disciplinary excellence and cross-disciplinary networking without any boundaries. Following the HCI-KDD approach, in combining the best of two worlds, it is aimed to support human intelligence with machine intelligence. This state-of-the-art survey is an output of the international HCI-KDD expert network and features 22 carefully selected and peer-reviewed chapters on hot topics in machine learning for health informatics; they discuss open problems and future challenges in order to stimulate further research and international progress in this field.

Download or read book User Modeling and Adaptation for Daily Routines written by Estefanía Martín and published by Springer Science & Business Media. This book was released on 2013-02-15 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: User Modeling and Adaptation for Daily Routines is motivated by the need to bring attention to how people with special needs can benefit from adaptive methods and techniques in their everyday lives. Assistive technologies, adaptive systems and context-aware applications are three well-established research fields. There is, in fact, a vast amount of literature that covers HCI-related issues in each area separately. However, the contributions in the intersection of these areas have been less visible, despite the fact that such synergies may have a great impact on improving daily living. Presenting a comprehensive review of state-of-the-art practices on user modeling and adaptation for people with special needs, as well as some reflections on the challenges that need to be addressed in this direction, topics covered within this volume include the analysis, design, implementation and evaluation of adaptive systems to assist users with special needs to take decisions and fulfil daily routine activities. Particular emphasis is paid to major trends in user modeling, ubiquitous adaptive support, diagnostic and accessibility, recommender systems, social interaction, designing and building adaptive assistants for daily routines, field studies and automated evaluation. Nine leading contributors write on key current research in the domain of adaptive applications for people with special needs, integrating and summarizing findings from the best known international research groups in these areas. User Modeling and Adaptation for Daily Routines highlights how adaptation technologies can ease daily living for all, and support sustainable high-quality healthcare, demographic ageing and social/economic inclusion. highlights how adaptation technologies can ease daily living for all, and support sustainable high-quality healthcare, demographic ageing and social/economic inclusion.

Download or read book Data Mining and Machine Learning Applications written by Rohit Raja and published by John Wiley & Sons. This book was released on 2022-01-26 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: DATA MINING AND MACHINE LEARNING APPLICATIONS The book elaborates in detail on the current needs of data mining and machine learning and promotes mutual understanding among research in different disciplines, thus facilitating research development and collaboration. Data, the latest currency of today’s world, is the new gold. In this new form of gold, the most beautiful jewels are data analytics and machine learning. Data mining and machine learning are considered interdisciplinary fields. Data mining is a subset of data analytics and machine learning involves the use of algorithms that automatically improve through experience based on data. Massive datasets can be classified and clustered to obtain accurate results. The most common technologies used include classification and clustering methods. Accuracy and error rates are calculated for regression and classification and clustering to find actual results through algorithms like support vector machines and neural networks with forward and backward propagation. Applications include fraud detection, image processing, medical diagnosis, weather prediction, e-commerce and so forth. The book features: A review of the state-of-the-art in data mining and machine learning, A review and description of the learning methods in human-computer interaction, Implementation strategies and future research directions used to meet the design and application requirements of several modern and real-time applications for a long time, The scope and implementation of a majority of data mining and machine learning strategies. A discussion of real-time problems. Audience Industry and academic researchers, scientists, and engineers in information technology, data science and machine and deep learning, as well as artificial intelligence more broadly.

Download or read book Trends in Practical Applications of Agents and Multiagent Systems written by Javier Bajo Pérez and published by Springer Science & Business Media. This book was released on 2013-04-20 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research on Agents and Multi-agent Systems has matured during the last decade and many effective applications of this technology are now deployed. PAAMS provides an international forum to presents and discuss the latest scientific developments and their effective applications, to assess the impact of the approach, and to facilitate technology transfer. PAAMS started as a local initiative, but since grown to become the international yearly platform to present, to discuss, and to disseminate the latest developments and the most important outcomes related to real-world applications. It provides a unique opportunity to bring multi-disciplinary experts, academics and practitioners together to Exchange their experience in the development and deployment of Agents and Multi-agents systems. PAAMS intends to bring together researchers and developers from industry and the academic world to report on the latest scientific and technical advances on the application of multi-agent systems, to discuss and debate the major issues, and to showcase the latest systems using agent based technology. It will promote a forum for discussion on how agent based techniques, methods and tools help system designers to accomplish the mapping between available agent technology and application needs. Other stakeholders should be rewarded with a better understanding of the potential and challenges of the agent-oriented approach. This edition of PAAMS special sessions is organized by the Bioinformatics, Intelligent System and Educational Technology Research Group (http://bisite.usal.es) of the University of Salamanca. The present edition was held in Salamanca, Spain, from 22nd to 24th May 2013.