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Recommender Systems Handbook
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-...
Social Data Analytics
This book is an introduction to social data analytics along with its challenges and opportunities in the age of Big Data and Artificial Intelligence. It focuses primarily on concepts, techniques and methods for organizing, curating, processing, analyzing, and visualizing big social data: from text to image and video analytics. It provides novel techniques in storytelling with social data to facilitate the knowledge and fact discovery. The book covers a large body of knowledge that will help practitioners and researchers in understanding the underlying concepts, problems, methods, tools and techniques involved in modern social data analytics. It also provides real-world applications of social...
Recommender Systems Handbook
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...
Netflix Recommends
Introduction -- Why we need film and series suggestions -- How algorithmic recommender systems work -- Cracking the code, part I : developing Netflix's recommendation algorithms -- Cracking the code, part II : unpacking Netflix's myth of big data -- How real people choose films and series -- Afterword : robot critics vs. human experts -- Appendix : designing the empirical audience study.
Fighting Terror in Cyberspace
As became apparent after the tragic events of September 11, 2001, terrorist groups are increasingly using the Internet as a communication and propaganda tool where they can safely communicate with their affiliates, coordinate action plans, raise funds, and introduce new supporters to their networks. This is evident from the large number of web sites run by different terrorist organizations, though the URLs and geographical locations of these web sites are frequently moved around the globe. The wide use of the Internet by terrorists makes some people think that the risk of a major cyber-attack against the communication infrastructure is low. However, this situation may change abruptly once th...
Security Informatics and Terrorism: Patrolling the Web
This work is intended to be of interest to counter-terrorism experts and professionals, to academic researchers in information systems, computer science, political science and public policy, and to graduate students in these areas. The goal of this book is to highlight several aspects of patrolling the Web that were raised and discussed by experts from different disciplines. The book includes academic studies from related technical fields, namely, computer science and information technology, the strategic point of view as presented by intelligence experts, and finally the practical point of view by experts from related industry describing lessons learned from practical efforts to tackle these problems. This volume is organized into four major parts: definition and analysis of the subject, data-mining techniques for terrorism informatics, other theoretical methods to detect terrorists on the Web, and practical relevant industrial experience on patrolling the Web.
Security Informatics and Terrorism
Intended to be of interest to counter-terrorism experts and professionals, to academic researchers in information systems, computer science, political science, and public policy, and to graduate students in these areas, this book highlights several aspects of patrolling the Web that were raised and discussed by experts from different disciplines.
Personalized Human-Computer Interaction
Personalized and adaptive systems employ user models to adapt content, services, interaction or navigation to individual users’ needs. User models can be inferred from implicitly observed information, such as the user’s interaction history or current location, or from explicitly entered information, such as user profile data or ratings. Applications of personalization include item recommendation, location-based services, learning assistance and the tailored selection of interaction modalities. With the transition from desktop computers to mobile devices and ubiquitous environments, the need for adapting to changing contexts is even more important. However, this also poses new challenges concerning privacy issues, user control, transparency, and explainability. In addition, user experience and other human factors are becoming increasingly important. This book describes foundations of user modeling, discusses user interaction as a basis for adaptivity, and showcases several personalization approaches in a variety of domains, including music recommendation, tourism, and accessible user interfaces.
Cyber Security Cryptography and Machine Learning
This book constitutes the proceedings of the first International Symposium on Cyber Security Cryptography and Machine Learning, held in Beer-Sheva, Israel, in June 2017. The 17 full and 4 short papers presented include cyber security; secure software development methodologies, formal methods semantics and verification of secure systems; fault tolerance, reliability, availability of distributed secure systems; game-theoretic approaches to secure computing; automatic recovery of self-stabilizing and self-organizing systems; communication, authentication and identification security; cyber security for mobile and Internet of things; cyber security of corporations; security and privacy for cloud, edge and fog computing; cryptography; cryptographic implementation analysis and construction; secure multi-party computation; privacy-enhancing technologies and anonymity; post-quantum cryptography and security; machine learning and big data; anomaly detection and malware identification; business intelligence and security; digital forensics; digital rights management; trust management and reputation systems; information retrieval, risk analysis, DoS.
MUBI and the Curation Model of Video on Demand
Subscription video on demand (SVOD) represents the fastest-growing means to consume films and series. Although market leaders Netflix and Amazon Prime have received much scholarly attention for the way that they use algorithms and big data to connect users to content, there is another significant, relatively unexamined model: curation-style services such as BFI Player, IFC Unlimited, the Criterion Channel or MUBI — the latter, which forms the focus of this book, claims to be the world's most subscribed independent video on demand service. These platforms take advantage of common anxieties about algorithms, cultural surplus and filter bubbles to promote discovery, human-generated recommenda...
