Modern Information Processing

Modern Information Processing

From Theory to Applications

1st Edition - February 8, 2006

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  • Editors: Bernadette Bouchon-Meunier, Giulianella Coletti, Ronald Yager
  • eBook ISBN: 9780080461694

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Description

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

Key Features

· 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.

Readership

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.

Table of Contents

  • Foreword. L.A. Zadeh


    Uncertainty


    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


    Preferences


    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


    Improving the K2 algorithm using association rule parameters, E. Lamma, F. Riguzzi, S. Storari


    Aggregation and Multi-Criteria Decision Making


    OWA aggregation on an interval argument and operative values, R. Yager


    On bi-capacity-based concordance rules in multicriteria decision making, A. Rolland


    Information Evaluation in fusion: Formalization of informal recommendations, L. Cholvy


    Application of uncertainty-based methods to fuse language identification expert decisions, J. Gutiérrez, J-L Rouas, R. Andre-Obrécht


    Intelligent multiattribute decision support model for triage, F. Burstein, J. San Pedro, L. Churilov, J.Wassertheil


    Interval-based multicriteria decision making, M. Ceberio, F. Modave


    A linguistic hierarchical evaluation model for engineering systems, L. Martínez, L. G. Perez, J. Liu, J.-B.o Yang, F. Herrera


    Knowledge Representation


    Non monotonic aggregates applying to fuzzy sets in flexible querying, P. Bosc, L. Liétard


    Fuzzy spatial data modeling: an extended bitmap approach, J. Verstraete, G. De Tré, A. Hallez


    Introducing l-specialization into the fuzzy EER model, G. Chen, L. Lin, X. Guo


    A logical reasoning framework for modelling and merging uncertain semi-structured information, A. Hunter, W. Liu


    Applied Domains


    Machine learning and the prediction of protein structure: the state of the art, R.Casadio, R. Calabrese, E. Capriotti, M. Compiani, P. Fariselli, P. Marani, L. Montanucci, P. L. Martelli, I. Rossi, G. Tasco


    Efficient and robust global amino-acid sequence alignment with uncertain evolutionary distance, M. Troffaes


    Classifying biomedical spectra using stochastic feature selection and parallelized multi-layer perceptrons, N.J. Pizzi, R.L. Somorjai, W. Pedrycs


    On the sensitivity of probabilistic networks to reliability characteristics, L. C. van der Gaag, S. Renooij


    Dominance of recognition of words presented on right or left eye –Comparison of Kanji and hiragana, T. Yamanoi, T. Yamazaki, J-L Vercher, E. Sanchez, M. Sugeno


    Hand posture recognition with the fuzzy glove, T. Allevard, E. Benoit, L. Foulloy


    Image retrieval by composition of regions, J.F. Omhover, M. Detyniecki


    Blind Image restoration from multiple views by IMAP estimation, M. Discepoli, I. Gerace, R. Pandolfi


    A combined feature extraction method for an electronic nose, I. Hristozov, B.Iliev, S. Eskiizmirliler


    Author Index.

Product details

  • No. of pages: 478
  • Language: English
  • Copyright: © Elsevier Science 2006
  • Published: February 8, 2006
  • Imprint: Elsevier Science
  • eBook ISBN: 9780080461694

About the Editors

Bernadette Bouchon-Meunier

Affiliations and Expertise

CNRS-UPMCS, LIP6, Paris, France

Giulianella Coletti

Affiliations and Expertise

University of Perugia, Italy

Ronald Yager

Dr. Ronald R. Yager is a researcher in computational intelligence and decision making under uncertainty and fuzzy logic. He is currently Director of the Machine Intelligence Institute and Professor of Information Systems at Iona College. He has been an active IEEE Fellow since 1997 for his contributions to the development of the theory of fuzzy logic. He is the Editor and Chief of the International Journal of Intelligent Systems, which serves as a forum for individuals interested in tapping into the vast theories based on intelligent systems construction. He has also been invited to serve on the Editorial Boards and Executive Advisory Boards for a number of International Journals, including IEEE Intelligent Systems, IEEE Transactions on Fuzzy Systems, and the Fuzzy Sets and Systems Journal.

Affiliations and Expertise

Iona College, Machine Intelligence Institute, New York, U.S.A.

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