Intelligent Systems For Information Processing From Representation To Applications
Download Intelligent Systems For Information Processing From Representation To Applications PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Intelligent Systems For Information Processing From Representation To Applications book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Intelligent Systems for Information Processing: From Representation to Applications
Intelligent systems are required to enhance the capacities being made available to us by the internet and other computer based technologies. The theory necessary to help providing solutions to difficult problems in the construction of intelligent systems are discussed. In particular, attention is paid to situations in which the available information and data may be imprecise, uncertain, incomplete or of a linguistic nature. Various methodologies to manage such information are discussed. Among these are the probabilistic, possibilistic, fuzzy, logical, evidential and network-based frameworks.One purpose of the book is not to consider these methodologies separately, but rather to consider how they can be used cooperatively to better represent the multiplicity of modes of information. Topics in the book include representation of imperfect knowledge, fundamental issues in uncertainty, reasoning, information retrieval, learning and mining, as well as various applications.Key Features:• Tools for construction of intelligent systems • Contributions by world leading experts • Fundamental issues and applications • New technologies for web searching • Methods for modeling uncertain information • Future directions in web technologies • Transversal to methods and domains
Modern Information Processing
Author: Bernadette Bouchon-Meunier
language: en
Publisher: Elsevier
Release Date: 2011-10-13
The volume "Modern Information Processing: From Theory to Applications," edited by Bernadette Bouchon-Meunier, Giulianella Coletti and Ronald Yager, is a collection of carefully selected papers drawn from the program of IPMU'04, which was held in Perugia, Italy. The book represents the cultural policy of IPMU conference which is not focused on narrow range of methodologies, but on the contrary welcomes all the theories for the management of uncertainty and aggregation of information in intelligent systems, providing a medium for the exchange of ideas between theoreticians and practitioners in these and related areas.The book is composed by 7 sections: UNCERTAINTYPREFERENCESCLASSIFICATION AND DATA MININGAGGREGATION AND MULTI-CRITERIA DECISION MAKINGKNOWLEDGE REPRESENTATION•The book contributes to enhancement of our ability to deal effectively with uncertainty in all of its manifestations. •The book can help to build brigs among theories and methods methods for the management of uncertainty. •The book addresses issues which have a position of centrality in our information-centric world. •The book presents interesting results devoted to representing knowledge: the goal is to capture the subtlety of human knowledge (richness) and to allow computer manipulation (formalization). •The book contributes to the goal: an efficient use of the information for a good decision strategy.APPLIED DOMAINS· The book contributes to enhancement of our ability to deal effectively with uncertainty in all of its manifestations.· The book can help to build brigs among theories and methods methods for the management of uncertainty.· The book addresses issues which have a position of centrality in our information-centric world.· The book presents interesting results devoted to representing knowledge: the goal is to capture the subtlety of human knowledge (richness) and to allow computer manipulation (formalization).· The book contributes to the goal: an efficient use of the information for a good decision strategy.
Axionomics
Axionomics presents a comprehensive, recursive framework that unifies axiomatic principles, atomic structures, quantum mechanics, and decentralized knowledge systems into a self-regulating, axiom-driven knowledge and energy economy. By integrating linguistic organization, artificial intelligence (AI), blockchain-backed verification, and decentralized scientific governance, this revolutionary model creates a seamless bridge between foundational principles and applied systems. Operating simultaneously across quantum, atomic, and macroscopic organizational scales, Axionomics leverages recursive feedback loops and self-referential processes to enable continuous adaptation and optimization. This dynamic, self-evolving architecture refines itself in response to new discoveries while preserving core axiomatic integrity, ensuring the stability of knowledge structures even in rapidly advancing scientific fields. By fostering interdisciplinary collaboration, Axionomics reshapes scientific inquiry, computational intelligence, and organizational governance. This system transcends conventional limitations, offering a self-optimizing knowledge ecosystem that harmonizes theory and practice, unlocking new frontiers in innovation, knowledge distribution, and decentralized intelligence networks. As a transformative model, Axionomics redefines how we understand, verify, and apply knowledge, setting the foundation for a future driven by recursive intelligence, axiomatic reasoning, and sustainable progress.