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Feature Engineering for Machine Learning and Data Analytics
Feature engineering plays a vital role in big data analytics. Machine learning and data mining algorithms cannot work without data. Little can be achieved if there are few features to represent the underlying data objects, and the quality of results of those algorithms largely depends on the quality of the available features. Feature Engineering for Machine Learning and Data Analytics provides a comprehensive introduction to feature engineering, including feature generation, feature extraction, feature transformation, feature selection, and feature analysis and evaluation. The book presents key concepts, methods, examples, and applications, as well as chapters on feature engineering for majo...
Foundations of Intelligent Systems
This book constitutes the refereed proceedings of the 16th International Symposium on Methodologies for Intelligent Systems, ISMIS 2006. The book presents 81 revised papers together with 3 invited papers. Topical sections include active media human-computer interaction, computational intelligence, intelligent agent technology, intelligent information retrieval, intelligent information systems, knowledge representation and integration, knowledge discovery and data mining, logic for AI and logic programming, machine learning, text mining, and Web intelligence.
Liabilities and Modern Artificial Intelligence
This book addresses how private law liability should be assigned in contexts where modern forms of AI are deployed. AI as a technology holds the potential to radically improve global society, yet the pace of its advancement far outstrips the pace at which legal systems are responding. This book explores legal approaches to AI, how AI should be legally characterised, and proposes an overarching theoretical liability framework termed the Tri-Phase AI Liability Model. This framework is flexible in nature and considers the type of AI, the context in which it is deployed, who has the most control over the AI system and the capacity of a deployed AI. In response, this book brings greatly needed clarity to the evolving landscape of AI governance, aiding in resolving existing and emerging private law challenges. This book is a timely response to the urgent need to resolve private law liabilities and will appeal to legal professionals, policy makers, and scholars looking to understand or contribute to the current and future governance of AI within private law.
Introduction to Description Logic
The first introductory textbook on description logics, relevant to computer science, knowledge representation and the semantic web.
Methodologies for Intelligent Systems
This volume contains papers selected for presentation at the Seventh International Symposium on Methodologies for Intelligent Systems (ISMIS '93), held at the Norwegian Institute of Technology, Trondheim, Norway, in June 1993. The volume includes six invited talks and 43 contributed papers organized under the following headings: logic for artificial intelligence, expert systems, intelligent databases, approximate reasoning, constraint programming, learning and adaptive systems, methodologies, knowledge representation, and manufacturing. Theinvited talks are: "On extended disjunctive logic programs" (J. Minker, C. Ruiz), "Towards intelligent databases" (F. Bry), "Methodologies for knowledge-based software engineering" (M. Lowry), "Modelling of industrial systems" (L. Ljung), "The many faces of inductive logic programming" (L. De Raedt, N. Lavrac), and "Systematic assessment of temporal reasoning methods for use in autonomous agents" (E. Sandewall).
