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Author: Xin Liu
Publisher: CRC Press
ISBN: 1482226677
Category : Computers
Languages : en
Pages : 227
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Book Description
Computational Trust Models and Machine Learning provides a detailed introduction to the concept of trust and its application in various computer science areas, including multi-agent systems, online social networks, and communication systems. Identifying trust modeling challenges that cannot be addressed by traditional approaches, this book:Explains
Author: Xin Liu
Publisher: CRC Press
ISBN: 1482226677
Category : Computers
Languages : en
Pages : 227
Get Book Here
Book Description
Computational Trust Models and Machine Learning provides a detailed introduction to the concept of trust and its application in various computer science areas, including multi-agent systems, online social networks, and communication systems. Identifying trust modeling challenges that cannot be addressed by traditional approaches, this book:Explains
Author: Khosrow-Pour, D.B.A., Mehdi
Publisher: IGI Global
ISBN: 1522573690
Category : Computers
Languages : en
Pages : 1221
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Book Description
As modern technologies continue to develop and evolve, the ability of users to adapt with new systems becomes a paramount concern. Research into new ways for humans to make use of advanced computers and other such technologies through artificial intelligence and computer simulation is necessary to fully realize the potential of tools in the 21st century. Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-Computer Interaction provides emerging research in advanced trends in robotics, AI, simulation, and human-computer interaction. Readers will learn about the positive applications of artificial intelligence and human-computer interaction in various disciples such as business and medicine. This book is a valuable resource for IT professionals, researchers, computer scientists, and researchers invested in assistive technologies, artificial intelligence, robotics, and computer simulation.
Author: Christiano Castelfranchi
Publisher: John Wiley & Sons
ISBN: 9780470519844
Category : Technology & Engineering
Languages : en
Pages : 386
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Book Description
This book provides an introduction, discussion, and formal-based modelling of trust theory and its applications in agent-based systems This book gives an accessible explanation of the importance of trust in human interaction and, in general, in autonomous cognitive agents including autonomous technologies. The authors explain the concepts of trust, and describe a principled, general theory of trust grounded on cognitive, cultural, institutional, technical, and normative solutions. This provides a strong base for the author’s discussion of role of trust in agent-based systems supporting human-computer interaction and distributed and virtual organizations or markets (multi-agent systems). Key Features: Provides an accessible introduction to trust, and its importance and applications in agent-based systems Proposes a principled, general theory of trust grounding on cognitive, cultural, institutional, technical, and normative solutions. Offers a clear, intuitive approach, and systematic integration of relevant issues Explains the dynamics of trust, and the relationship between trust and security Offers operational definitions and models directly applicable both in technical and experimental domains Includes a critical examination of trust models in economics, philosophy, psychology, sociology, and AI This book will be a valuable reference for researchers and advanced students focused on information and communication technologies (computer science, artificial intelligence, organizational sciences, and knowledge management etc.), as well as Web-site and robotics designers, and for scholars working on human, social, and cultural aspects of technology. Professionals of ecommerce systems and peer-to-peer systems will also find this text of interest.
Author: Young Ae Kim
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
With the proliferation of online communities and Person-to-Person (P2P) online service markets, the deployment of knowledge, skills, experiences and user generated contents services are generally facilitated among service users and service providers. In online service markets where well-established intermediaries are often eliminated, the success of social interactions for service exchange among completely unknown users depends on 'trust' of a service user for a service provider. Therefore, providing a satisfactory trust model to evaluate the quality of services and to recommend personalized trustworthy service providers is vital for a successful online community and P2P online service market. However, finding trustworthy service providers for each individual user is challenging because of the lack of direct experiences and the subjective property of trust. In order to resolve the challenges, current research on trust prediction strongly relies on a web of trust, which is directly collected from users. However, the web of trust is not always available in online communities and, even when it is available, it is often too sparse to accurately predict the trust value between two unacquainted people. In this paper, we propose a computational trust model to predict trust connectivity based on service providers' expertise (local trust from direct experiences and a reputation) and service users' affinity for certain contexts (topics). The approach used item rating data that is available and much more dense than direct trust data. In experiments with a real-world dataset, we show that our model can predict trust connectivity with a high degree of accuracy. The proposed computational trust framework can be applied to any type of online communities or P2P online service markets with a rating system.
Author: Simon Rogers
Publisher: CRC Press
ISBN: 1498738540
Category : Computers
Languages : en
Pages : 428
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Book Description
Introduces the main algorithms and ideas that underpin machine learning techniques and applications Keeps mathematical prerequisites to a minimum, providing mathematical explanations in comment boxes and highlighting important equations Covers modern machine learning research and techniques Includes three new chapters on Markov Chain Monte Carlo techniques, Classification and Regression with Gaussian Processes, and Dirichlet Process models Offers Python, R, and MATLAB code on accompanying website: http://www.dcs.gla.ac.uk/~srogers/firstcourseml/"
Author: Masashi Sugiyama
Publisher: CRC Press
ISBN: 1439856907
Category : Business & Economics
Languages : en
Pages : 206
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Book Description
Reinforcement learning (RL) is a framework for decision making in unknown environments based on a large amount of data. Several practical RL applications for business intelligence, plant control, and gaming have been successfully explored in recent years. Providing an accessible introduction to the field, this book covers model-based and model-free approaches, policy iteration, and policy search methods. It presents illustrative examples and state-of-the-art results, including dimensionality reduction in RL and risk-sensitive RL. The book provides a bridge between RL and data mining and machine learning research.
Author: Mark Stamp
Publisher: CRC Press
ISBN: 1351818066
Category : Business & Economics
Languages : en
Pages : 274
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Book Description
Introduction to Machine Learning with Applications in Information Security provides a class-tested introduction to a wide variety of machine learning algorithms, reinforced through realistic applications. The book is accessible and doesn’t prove theorems, or otherwise dwell on mathematical theory. The goal is to present topics at an intuitive level, with just enough detail to clarify the underlying concepts. The book covers core machine learning topics in-depth, including Hidden Markov Models, Principal Component Analysis, Support Vector Machines, and Clustering. It also includes coverage of Nearest Neighbors, Neural Networks, Boosting and AdaBoost, Random Forests, Linear Discriminant Analysis, Vector Quantization, Naive Bayes, Regression Analysis, Conditional Random Fields, and Data Analysis. Most of the examples in the book are drawn from the field of information security, with many of the machine learning applications specifically focused on malware. The applications presented are designed to demystify machine learning techniques by providing straightforward scenarios. Many of the exercises in this book require some programming, and basic computing concepts are assumed in a few of the application sections. However, anyone with a modest amount of programming experience should have no trouble with this aspect of the book. Instructor resources, including PowerPoint slides, lecture videos, and other relevant material are provided on an accompanying website: http://www.cs.sjsu.edu/~stamp/ML/. For the reader’s benefit, the figures in the book are also available in electronic form, and in color. About the Author Mark Stamp has been a Professor of Computer Science at San Jose State University since 2002. Prior to that, he worked at the National Security Agency (NSA) for seven years, and a Silicon Valley startup company for two years. He received his Ph.D. from Texas Tech University in 1992. His love affair with machine learning began in the early 1990s, when he was working at the NSA, and continues today at SJSU, where he has supervised vast numbers of master’s student projects, most of which involve a combination of information security and machine learning.
Author: Ricardo Armentano
Publisher: CRC Press
ISBN: 1351652095
Category : Mathematics
Languages : en
Pages : 448
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Book Description
This book provides a dual perspective on the Internet of Things and ubiquitous computing, along with their applications in healthcare and smart cities. It also covers other interdisciplinary aspects of the Internet of Things like big data, embedded Systems and wireless Sensor Networks. Detailed coverage of the underlying architecture, framework, and state-of the art methodologies form the core of the book.
Author: Costin Badica
Publisher: Springer
ISBN: 3319488295
Category : Technology & Engineering
Languages : en
Pages : 254
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Book Description
This book presents the combined peer-reviewed proceedings of the tenth International Symposium on Intelligent Distributed Computing (IDC’2016), which was held in Paris, France from October 10th to 12th, 2016. The 23 contributions address a range of topics related to theory and application of intelligent distributed computing, including: Intelligent Distributed Agent-Based Systems, Ambient Intelligence and Social Networks, Computational Sustainability, Intelligent Distributed Knowledge Representation and Processing, Smart Networks, Networked Intelligence and Intelligent Distributed Applications, amongst others.
Author: Irina Rish
Publisher: CRC Press
ISBN: 1439828709
Category : Business & Economics
Languages : en
Pages : 250
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Book Description
Sparse models are particularly useful in scientific applications, such as biomarker discovery in genetic or neuroimaging data, where the interpretability of a predictive model is essential. Sparsity can also dramatically improve the cost efficiency of signal processing.Sparse Modeling: Theory, Algorithms, and Applications provides an introduction t