Ai Ia 2019 Advances In Artificial Intelligence

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Ai Ia 2019 Advances In Artificial Intelligence


Ai Ia 2019 Advances In Artificial Intelligence
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Ai Ia 2019 Advances In Artificial Intelligence


Ai Ia 2019 Advances In Artificial Intelligence
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Author : Mario Alviano
language : en
Publisher: Springer
Release Date : 2019-11-17

Ai Ia 2019 Advances In Artificial Intelligence written by Mario Alviano and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-17 with Computers categories.


This book constitutes the proceedings of the XVIIIth International Conference of the Italian Association for Artificial Intelligence, AI*IA 2019, held in Rende, Italy, in November 2019. The 41 full papers were carefully reviewed and selected from 67 submissions. The papers have been organized in the following topical sections: Knowledge Representation for AI, AI and Computation, Machine Learning for AI, and AI and Humans.

Innovation In Medicine And Healthcare


Innovation In Medicine And Healthcare
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Author : Yen-Wei Chen
language : en
Publisher: Springer Nature
Release Date : 2021-06-05

Innovation In Medicine And Healthcare written by Yen-Wei Chen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-05 with Technology & Engineering categories.


This book presents the proceedings of the KES International Conferences on Innovation in Medicine and Healthcare (KES-InMed-21), held virtually on June 14–16, 2021. Covering a number of key areas, including digital IT architecture in healthcare; advanced ICT for medicine and healthcare; biomedical engineering, trends, research and technologies; and healthcare support systems, this book is a valuable resource for researchers, managers, industrialists and anyone wishing to gain an overview of the latest research in these fields.

Artificial Intelligence For High Energy Physics


Artificial Intelligence For High Energy Physics
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Author : Paolo Calafiura
language : en
Publisher: World Scientific
Release Date : 2022-01-05

Artificial Intelligence For High Energy Physics written by Paolo Calafiura and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-05 with Science categories.


The Higgs boson discovery at the Large Hadron Collider in 2012 relied on boosted decision trees. Since then, high energy physics (HEP) has applied modern machine learning (ML) techniques to all stages of the data analysis pipeline, from raw data processing to statistical analysis. The unique requirements of HEP data analysis, the availability of high-quality simulators, the complexity of the data structures (which rarely are image-like), the control of uncertainties expected from scientific measurements, and the exabyte-scale datasets require the development of HEP-specific ML techniques. While these developments proceed at full speed along many paths, the nineteen reviews in this book offer a self-contained, pedagogical introduction to ML models' real-life applications in HEP, written by some of the foremost experts in their area.

Recent Trends In Learning From Data


Recent Trends In Learning From Data
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Author : Luca Oneto
language : en
Publisher: Springer Nature
Release Date : 2020-04-03

Recent Trends In Learning From Data written by Luca Oneto and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-03 with Technology & Engineering categories.


This book offers a timely snapshot and extensive practical and theoretical insights into the topic of learning from data. Based on the tutorials presented at the INNS Big Data and Deep Learning Conference, INNSBDDL2019, held on April 16-18, 2019, in Sestri Levante, Italy, the respective chapters cover advanced neural networks, deep architectures, and supervised and reinforcement machine learning models. They describe important theoretical concepts, presenting in detail all the necessary mathematical formalizations, and offer essential guidance on their use in current big data research.

International Conference On Artificial Intelligence Advances And Applications 2019


International Conference On Artificial Intelligence Advances And Applications 2019
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Author : Garima Mathur
language : en
Publisher: Springer Nature
Release Date : 2020-02-28

International Conference On Artificial Intelligence Advances And Applications 2019 written by Garima Mathur and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-28 with Technology & Engineering categories.


This book introduces research presented at the “International Conference on Artificial Intelligence: Advances and Applications-2019 (ICAIAA 2019),” a two-day conference and workshop bringing together leading academicians, researchers as well as students to share their experiences and findings on all aspects of engineering applications of artificial intelligence. The book covers research in the areas of artificial intelligence, machine learning, and deep learning applications in health care, agriculture, business and security. It also includes research in core concepts of computer networks, intelligent system design and deployment, real-time systems, WSN, sensors and sensor nodes, SDN and NFV. As such it is a valuable resource for students, academics and practitioners in industry working on AI applications.

Artificial Intelligence For Customer Relationship Management


Artificial Intelligence For Customer Relationship Management
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Author : Boris Galitsky
language : en
Publisher: Springer Nature
Release Date : 2020-12-23

Artificial Intelligence For Customer Relationship Management written by Boris Galitsky and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-23 with Computers categories.


The second volume of this research monograph describes a number of applications of Artificial Intelligence in the field of Customer Relationship Management with the focus of solving customer problems. We design a system that tries to understand the customer complaint, his mood, and what can be done to resolve an issue with the product or service. To solve a customer problem efficiently, we maintain a dialogue with the customer so that the problem can be clarified and multiple ways to fix it can be sought. We introduce dialogue management based on discourse analysis: a systematic linguistic way to handle the thought process of the author of the content to be delivered. We analyze user sentiments and personal traits to tailor dialogue management to individual customers. We also design a number of dialogue scenarios for CRM with replies following certain patterns and propose virtual and social dialogues for various modalities of communication with a customer. After we learn to detect fake content, deception and hypocrisy, we examine the domain of customer complaints. We simulate mental states, attitudes and emotions of a complainant and try to predict his behavior. Having suggested graph-based formal representations of complaint scenarios, we machine-learn them to identify the best action the customer support organization can chose to retain the complainant as a customer.

Knowledge Graphs For Explainable Artificial Intelligence Foundations Applications And Challenges


Knowledge Graphs For Explainable Artificial Intelligence Foundations Applications And Challenges
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Author : I. Tiddi
language : en
Publisher: IOS Press
Release Date : 2020-05-06

Knowledge Graphs For Explainable Artificial Intelligence Foundations Applications And Challenges written by I. Tiddi and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-06 with Computers categories.


The latest advances in Artificial Intelligence and (deep) Machine Learning in particular revealed a major drawback of modern intelligent systems, namely the inability to explain their decisions in a way that humans can easily understand. While eXplainable AI rapidly became an active area of research in response to this need for improved understandability and trustworthiness, the field of Knowledge Representation and Reasoning (KRR) has on the other hand a long-standing tradition in managing information in a symbolic, human-understandable form. This book provides the first comprehensive collection of research contributions on the role of knowledge graphs for eXplainable AI (KG4XAI), and the papers included here present academic and industrial research focused on the theory, methods and implementations of AI systems that use structured knowledge to generate reliable explanations. Introductory material on knowledge graphs is included for those readers with only a minimal background in the field, as well as specific chapters devoted to advanced methods, applications and case-studies that use knowledge graphs as a part of knowledge-based, explainable systems (KBX-systems). The final chapters explore current challenges and future research directions in the area of knowledge graphs for eXplainable AI. The book not only provides a scholarly, state-of-the-art overview of research in this subject area, but also fosters the hybrid combination of symbolic and subsymbolic AI methods, and will be of interest to all those working in the field.