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Book
Description Logics in Multimedia Reasoning
Author:
ISBN: 3319540661 3319540653 Year: 2017 Publisher: Cham : Springer International Publishing : Imprint: Springer,

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Abstract

This book illustrates how to use description logic-based formalisms to their full potential in the creation, indexing, and reuse of multimedia semantics. To do so, it introduces researchers to multimedia semantics by providing an in-depth review of state-of-the-art standards, technologies, ontologies, and software tools. It draws attention to the importance of formal grounding in the knowledge representation of multimedia objects, the potential of multimedia reasoning in intelligent multimedia applications, and presents both theoretical discussions and best practices in multimedia ontology engineering. Readers already familiar with mathematical logic, Internet, and multimedia fundamentals will learn to develop formally grounded multimedia ontologies, and map concept definitions to high-level descriptors. The core reasoning tasks, reasoning algorithms, and industry-leading reasoners are presented, while scene interpretation via reasoning is also demonstrated. Overall, this book offers readers an essential introduction to the formal grounding of web ontologies, as well as a comprehensive collection and review of description logics (DLs) from the perspectives of expressivity and reasoning complexity. It covers best practices for developing multimedia ontologies with formal grounding to guarantee decidability and obtain the desired level of expressivity while maximizing the reasoning potential. The capabilities of such multimedia ontologies are demonstrated by DL implementations with an emphasis on multimedia reasoning applications.

Keywords

Computer science. --- Mathematical logic. --- Computer science --- Artificial intelligence. --- Image processing. --- Computer mathematics. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Mathematical Logic and Formal Languages. --- Image Processing and Computer Vision. --- Discrete Mathematics in Computer Science. --- Mathematical Applications in Computer Science. --- Mathematics. --- Computer mathematics --- Discrete mathematics --- Electronic data processing --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Algebra of logic --- Logic, Universal --- Mathematical logic --- Symbolic and mathematical logic --- Symbolic logic --- Mathematics --- Algebra, Abstract --- Metamathematics --- Set theory --- Syllogism --- Informatics --- Science --- Computer vision. --- Computational complexity. --- Artificial Intelligence. --- Complexity, Computational --- Machine vision --- Vision, Computer --- Artificial intelligence --- Image processing --- Pattern recognition systems --- Optical data processing. --- Computer science—Mathematics. --- Optical computing --- Visual data processing --- Integrated optics --- Photonics --- Computers --- Optical equipment


Book
AI in Cybersecurity
Author:
ISBN: 3319988425 3319988417 Year: 2019 Publisher: Cham : Springer International Publishing : Imprint: Springer,

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Abstract

This book presents a collection of state-of-the-art AI approaches to cybersecurity and cyberthreat intelligence, offering strategic defense mechanisms for malware, addressing cybercrime, and assessing vulnerabilities to yield proactive rather than reactive countermeasures. The current variety and scope of cybersecurity threats far exceed the capabilities of even the most skilled security professionals. In addition, analyzing yesterday’s security incidents no longer enables experts to predict and prevent tomorrow’s attacks, which necessitates approaches that go far beyond identifying known threats. Nevertheless, there are promising avenues: complex behavior matching can isolate threats based on the actions taken, while machine learning can help detect anomalies, prevent malware infections, discover signs of illicit activities, and protect assets from hackers. In turn, knowledge representation enables automated reasoning over network data, helping achieve cybersituational awareness. Bringing together contributions by high-caliber experts, this book suggests new research directions in this critical and rapidly growing field.

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