This timely volume combines experimental and theoretical research on big data recommender systems to help computer scientists develop new concepts and methodologies for complex applications. It includes original scientific contributions in the form of theoretical foundations, comparative analysis, surveys, case studies, techniques and tools. The authors give special attention to key topics such as data filtering and cleaning techniques for recommendations, novelty and diversity, privacy issues, security threats and their mitigation, trust, cold start, sparsity, scalability, application domains, and recommender system evaluations.

This book focuses on recent advances and future trends in the methods and applications of technologies that are used in neuroscience for the evaluation, diagnosis and treatment of neurological diseases and conditions or for the improvement of quality of life. The editors have assembled contributions from a range of international experts, to bring together key topics in neurotechnology, neuroengineering, and neurorehabilitation. The book explores biomedical signal processing, neuroimaging acquisition and analysis, computational intelligence, virtual and augmented reality, biometrics, machine learning and neurorobotics, human machine interaction, mobile apps and discusses ways in which these neural technologies can be used as diagnostic tools, research methods, treatment modalities, as well as in devices and apps in everyday life.