Human-Centered Artificial Intelligence
Human-Centered Artificial Intelligence

Author: Chang S. Nam

Publisher: Elsevier

Published: 2022-05-18

Total Pages: 312

ISBN-13: 0323856489

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Human-Centered Artificial Intelligence: Research and Applications presents current theories, fundamentals, techniques and diverse applications of human-centered AI. Sections address the question, "are AI models explainable, interpretable and understandable?, introduce readers to the design and development process, including mind perception and human interfaces, explore various applications of human-centered AI, including human-robot interaction, healthcare and decision-making, and more. As human-centered AI aims to push the boundaries of previously limited AI solutions to bridge the gap between machine and human, this book is an ideal update on the latest advances. Presents extensive research on human-centered AI technology Provides different methods and techniques used to investigate human-AI interaction Discusses open questions and challenges in trust within human-centered AI Explores how human-centered AI changes and operates in human-machine interactions

Information Processing and Management
Information Processing and Management

Author: Vinu V Das

Publisher: Springer Science & Business Media

Published: 2010-04-01

Total Pages: 693

ISBN-13: 3642122132

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It is my pleasure to write the preface for Information Processing and Management. This book aims to bring together innovative results and new research trends in inf- mation processing, computer science and management engineering. If an information processing system is able to perform useful actions for an obj- tive in a given domain, it is because the system knows something about that domain. The more knowledge it has, the more useful it can be to its users. Without that kno- edge, the system itself is useless. In the information systems field, there is conceptual modeling for the activity that elicits and describes the general knowledge a particular information system needs to know. The main objective of conceptual modeling is to obtain that description, which is called a conceptual schema. Conceptual schemas are written in languages called conceptual modeling languages. Conceptual modeling is an important part of requi- ments engineering, the first and most important phase in the development of an inf- mation system.

Information Processing and Management of Uncertainty
Information Processing and Management of Uncertainty

Author: Anne Laurent

Publisher: Springer

Published: 2014-07-17

Total Pages: 636

ISBN-13: 3319087959

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These three volumes (CCIS 442, 443, 444) constitute the proceedings of the 15th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2014, held in Montpellier, France, July 15-19, 2014. The 180 revised full papers presented together with five invited talks were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on uncertainty and imprecision on the web of data; decision support and uncertainty management in agri-environment; fuzzy implications; clustering; fuzzy measures and integrals; non-classical logics; data analysis; real-world applications; aggregation; probabilistic networks; recommendation systems and social networks; fuzzy systems; fuzzy logic in boolean framework; management of uncertainty in social networks; from different to same, from imitation to analogy; soft computing and sensory analysis; database systems; fuzzy set theory; measurement and sensory information; aggregation; formal methods for vagueness and uncertainty in a many-valued realm; graduality; preferences; uncertainty management in machine learning; philosophy and history of soft computing; soft computing and sensory analysis; similarity analysis; fuzzy logic, formal concept analysis and rough set; intelligent databases and information systems; theory of evidence; aggregation functions; big data - the role of fuzzy methods; imprecise probabilities: from foundations to applications; multinomial logistic regression on Markov chains for crop rotation modelling; intelligent measurement and control for nonlinear systems.

The Information Processing Theory of Organization
The Information Processing Theory of Organization

Author: John L. Kmetz

Publisher: Routledge

Published: 2018-11-09

Total Pages: 345

ISBN-13: 0429780834

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First published in 1998, revised in 2021, this volume develops and tests an information-processing model of organization, within the context of the accession of a new generation of a production technology. The model conceptualizes organizations as systems which accomplish their objectives through the processing of information. The book begins with the conceptual basis of the theory, developing the fundamental concepts of information, information processing, and technology. The accession of an automatic avionics tester during the 1970s and 1980s is the change in production technology used to test the theory. The theory is tested by mapping and analysing performance with a three-wave longitudinal field experiment and objective performance measures in the workflow of a very complex system, the U.S. Navy’s avionics maintenance organization. The information processing capacity of the system is shown to be the primary determinant of system performance, with or without the use of information technology. Additional support for the theory comes from newer test and information technologies deployed in the 1980s and 1990s. Implications of this theory for current generations of test technology are provided in the final chapters, along with further development of the theory and its general application to many types of organizations.

Information Processing and Management of Uncertainty in Knowledge-Based Systems
Information Processing and Management of Uncertainty in Knowledge-Based Systems

Author: Eyke Hüllermeier

Publisher: Springer

Published: 2010-06-29

Total Pages: 786

ISBN-13: 3642140556

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The International Conference on Information Processing and Management of - certainty in Knowledge-Based Systems, IPMU, is organized every two years with the aim of bringing together scientists working on methods for the management of uncertainty and aggregation of information in intelligent systems. Since 1986, this conference has been providing a forum for the exchange of ideas between th theoreticians and practitioners working in these areas and related ?elds. The 13 IPMU conference took place in Dortmund, Germany, June 28–July 2, 2010. This volume contains 79 papers selected through a rigorous reviewing process. The contributions re?ect the richness of research on topics within the scope of the conference and represent several important developments, speci?cally focused on theoretical foundations and methods for information processing and management of uncertainty in knowledge-based systems. We were delighted that Melanie Mitchell (Portland State University, USA), Nihkil R. Pal (Indian Statistical Institute), Bernhard Sch ̈ olkopf (Max Planck I- titute for Biological Cybernetics, Tubing ̈ en, Germany) and Wolfgang Wahlster (German Research Center for Arti?cial Intelligence, Saarbruc ̈ ken) accepted our invitations to present keynote lectures. Jim Bezdek received the Kamp ́ede F ́ eriet Award, granted every two years on the occasion of the IPMU conference, in view of his eminent research contributions to the handling of uncertainty in clustering, data analysis and pattern recognition.

Information Processing and Management of Uncertainty in Knowledge-Based Systems
Information Processing and Management of Uncertainty in Knowledge-Based Systems

Author: Joao Paulo Carvalho

Publisher: Springer

Published: 2016-06-10

Total Pages: 840

ISBN-13: 3319405810

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This two volume set (CCIS 610 and 611) constitute the proceedings of the 16th International Conference on Information processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2016, held in Eindhoven, The Netherlands, in June 2016. The 127 revised full papers presented together with four invited talks were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on fuzzy measures and integrals; uncertainty quantification with imprecise probability; textual data processing; belief functions theory and its applications; graphical models; fuzzy implications functions; applications in medicine and bioinformatics; real-world applications; soft computing for image processing; clustering; fuzzy logic, formal concept analysis and rough sets; graded and many-valued modal logics; imperfect databases; multiple criteria decision methods; argumentation and belief revision; databases and information systems; conceptual aspects of data aggregation and complex data fusion; fuzzy sets and fuzzy logic; decision support; comparison measures; machine learning; social data processing; temporal data processing; aggregation.

Information Processing and Management of Uncertainty in Knowledge-Based Systems
Information Processing and Management of Uncertainty in Knowledge-Based Systems

Author: Marie-Jeanne Lesot

Publisher: Springer Nature

Published: 2020-06-05

Total Pages: 816

ISBN-13: 3030501434

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This three volume set (CCIS 1237-1239) constitutes the proceedings of the 18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2020, in June 2020. The conference was scheduled to take place in Lisbon, Portugal, at University of Lisbon, but due to COVID-19 pandemic it was held virtually. The 173 papers were carefully reviewed and selected from 213 submissions. The papers are organized in topical sections: homage to Enrique Ruspini; invited talks; foundations and mathematics; decision making, preferences and votes; optimization and uncertainty; games; real world applications; knowledge processing and creation; machine learning I; machine learning II; XAI; image processing; temporal data processing; text analysis and processing; fuzzy interval analysis; theoretical and applied aspects of imprecise probabilities; similarities in artificial intelligence; belief function theory and its applications; aggregation: theory and practice; aggregation: pre-aggregation functions and other generalizations of monotonicity; aggregation: aggregation of different data structures; fuzzy methods in data mining and knowledge discovery; computational intelligence for logistics and transportation problems; fuzzy implication functions; soft methods in statistics and data analysis; image understanding and explainable AI; fuzzy and generalized quantifier theory; mathematical methods towards dealing with uncertainty in applied sciences; statistical image processing and analysis, with applications in neuroimaging; interval uncertainty; discrete models and computational intelligence; current techniques to model, process and describe time series; mathematical fuzzy logic and graded reasoning models; formal concept analysis, rough sets, general operators and related topics; computational intelligence methods in information modelling, representation and processing.

Information Processing and Management of Uncertainty in Knowledge-Based Systems
Information Processing and Management of Uncertainty in Knowledge-Based Systems

Author: Davide Ciucci

Publisher: Springer Nature

Published: 2022-07-04

Total Pages: 825

ISBN-13: 3031089715

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This two-volume set (CCIS 1601-1602) constitutes the proceedings of the 19th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2021, held in Milan, Italy, in July 2022. The 124 papers were carefully reviewed and selected from 188 submissions. The papers are organized in topical sections as follows: aggregation theory beyond the unit interval; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy mathematical analysis and its applications; generalized sets and operators; information fusion techniques based on aggregation functions, pre-aggregation functions, and their generalizations; interval uncertainty; knowledge acquisition, representation and reasoning; logical structures of opposition and logical syllogisms; mathematical fuzzy logics; theoretical and applied aspects of imprecise probabilities; data science and machine learning; decision making modeling and applications; e-health; fuzzy methods in data mining and knowledge discovery; soft computing and artificia intelligence techniques in image processing; soft methods in statistics and data analysis; uncertainty, heterogeneity, reliability and explainability in AI; weak and cautious supervised learning.

Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications
Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications

Author: Jesús Medina

Publisher: Springer

Published: 2018-05-29

Total Pages: 773

ISBN-13: 3319914790

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This three volume set (CCIS 853-855) constitutes the proceedings of the 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2017, held in Cádiz, Spain, in June 2018. The 193 revised full papers were carefully reviewed and selected from 383 submissions. The papers are organized in topical sections on advances on explainable artificial intelligence; aggregation operators, fuzzy metrics and applications; belief function theory and its applications; current techniques to model, process and describe time series; discrete models and computational intelligence; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy logic and artificial intelligence problems; fuzzy mathematical analysis and applications; fuzzy methods in data mining and knowledge discovery; fuzzy transforms: theory and applications to data analysis and image processing; imprecise probabilities: foundations and applications; mathematical fuzzy logic, mathematical morphology; measures of comparison and entropies for fuzzy sets and their extensions; new trends in data aggregation; pre-aggregation functions and generalized forms of monotonicity; rough and fuzzy similarity modelling tools; soft computing for decision making in uncertainty; soft computing in information retrieval and sentiment analysis; tri-partitions and uncertainty; decision making modeling and applications; logical methods in mining knowledge from big data; metaheuristics and machine learning; optimization models for modern analytics; uncertainty in medicine; uncertainty in Video/Image Processing (UVIP).