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:
UNCERTAINTY PREFERENCES CLASSIFICATION AND DATA MINING AGGREGATION AND MULTI-CRITERIA DECISION MAKING KNOWLEDGE 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.
Researchers oriented to theory and application of methods for handling partial knowledge in intelligent systems. Also for Ph.D. students in mathematics and computer science. Nevertheless, the book is intended for a wider audience ranging from graduate students with proper background in mathematics and/or informatics.
Foreword. L.A. Zadeh
Entropies, Characterizations, Applications and Some History, J. Aczél
Belief function theory on the continuous space with an application to model based classification, B. Ristic, P.Smets
Independence in conditional possibility theory, G. Coletti, B. Vantaggi
Joint treatment of imprecision and randomness in uncertainty propagation, C. Baudrit, D. Dubois, D. Guyonnet, H. Fargier
Consistency of probabilistic transformations of belief functions, M. Daniel
Randomization and uncertain inference, H. E. Kyburg, Jr., C. M. Teng
An empirical complexity study for a 2CPA solver, M. Baioletti, A. Capotorti, S. Tulipani
Consistency in preference modelling, J-L. García-Lapresta, J. Montero
Transitive decomposition of min-transitive fuzzy preference relations, S. Díaz, B. De Baets, S. Montes
Decision making with fuzzy ternary relations, S. Ovchinnikov
New Consistency properties for preference relations, F. Chiclana, E. Herrera-Viedma, F. Herrera
Management of uncertainty orderings through ASP, A. Capotorti, A. Formisano
Classification and Data Mining
Automating the quality assurance of an on-line knowledge-based classifier by fusing multiple off-line classifiers, P. Bonissone
Qualitative classification with possibilistic decision trees, N. Ben Amor, S. Benferhat, Z.Elouedi
Discovery of abstract knowledge from non-atomic attribute values in fuzzy relations, R. A. Angryk, F. E. Petry
Kernel-based outlier preserving clustering with representativity coefficients, M.J. Lesot
Fuzzy C-medoids clustering models for time-varying data, R. Coppi, P. D’Urso, P. Giordani
- No. of pages:
- © Elsevier Science 2006
- 8th February 2006
- Elsevier Science
- eBook ISBN:
- Hardcover ISBN:
CNRS-UPMCS, LIP6, Paris, France
University of Perugia, Italy
Iona College, Machine Intelligence Institute, New York, U.S.A.