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Intelligent Systems for Information Processing: From Representation to Applications B. Bouchon-Meunier (CNRS-UPMC, Paris, France)

Intelligent Systems for Information Processing: From Representation to Applications By B. Bouchon-Meunier (CNRS-UPMC, Paris, France)

Intelligent Systems for Information Processing: From Representation to Applications by B. Bouchon-Meunier (CNRS-UPMC, Paris, France)


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Summary

Discusses the theory necessary to help providing solutions to difficult problems in the construction of intelligent systems. This work covers topics that include representation of imperfect knowledge, fundamental issues in uncertainty, reasoning, information retrieval, learning and mining, as well as various applications.

Intelligent Systems for Information Processing: From Representation to Applications Summary

Intelligent Systems for Information Processing: From Representation to Applications by B. Bouchon-Meunier (CNRS-UPMC, Paris, France)

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

About B. Bouchon-Meunier (CNRS-UPMC, Paris, France)

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.

Table of Contents

Perception-based Information ProcessingToward a Perception-Based Theory of Probabilistic Reasoning with Imprecise Probabilities (L.A. Zadeh).Representing KnowledgeRough Set Uncertainty in an Object Oriented Data Model(T. Beaubouef, F.E. Petry).On the Representation of Fuzzy Spatial Relations in Robot Maps(I. Bloch, A. Saffiotti).Fuzzy Between Operators in the Framework of Fuzzy Orderings(U. Bodenhofer).A Step towards Conceptually Improving Takagi-Sugeno's Approximation(S. Guadarrama, E. Trillas, J. Gutierrez, F. Fernandez).Combining Heterogeneous Information in Group Decision Making(F. Herrera, E. Herrera-Viedma, L. Martinez, P.J. Sanchez).Function Approximation by Fuzzy Rough Sets(M. Inuiguchi, T. Tanino).Retrieving InformationQuery Aggregation Reflecting Domain-knowledge(T. Andreasen).Modelling of Fuzzy and Uncertain Spatio-Temporal Information in Databases: A Constraint-based Approach(G. de Tre, R. de Caluwe, A. Hallez, J.Verstraete).A General Framework for Meta-search based on Query-weighting and Numerical Aggregation Operators(M. Gomez, C. Abasolo).On the Comparison of Aggregates over Fuzzy Sets(P. Bosc, O. Pivert, L. Lietard).Towards an Intelligent Text Categorization for Web Resources: An Implementation(S. Zadrozny, K. Lawcewicz, J. Kacprzyk).ReasoningPrototype Based Reasoning and Fuzzy Modeling(R.R. Yager).Gradual Handling of Contradiction in Argumentation Frameworks(C. Cayrol, M.C. Lagasquie).Coherent Conditional Probability as a Tool for Default Reasoning(G. Coletti, R. Scozzafava, B. Vantaggi).Detecting Conflict-Free Assumption-Based Knowledge Bases(R. Haenni).UncertaintyTheory of Belief Functions: History and Prospects(A.P. Dempster).Towards Another Logical Interpretation of Theory of Evidence and a New Combination Rule(L. Cholvy).Uncertainty, Type-2 Fuzzy Sets, and Footprints of Uncertainty(J. M. Mendel).Rough Sets, Bayes' Theorem and Flow Graphs(Z. Pawlak).Belief Revision as Combinatorial Optimization(A. Ramer).Showing why Measures of Quantified Beliefs are Belief Functions(Ph. Smets).Extension of Coherent Lower Previsions to Unbounded Random Variables(M. C.M. Troffaes, G. de Cooman).Learning and MiningClustering of Proximity Data using Belief Functions(Th. Denoeux, M. Masson).A Hierarchical Linguistic Clustering Algorithm for Prototype Induction(L. Gonzalez Rodriguez, J. Lawry, J.F. Baldwin).A Multiobjective Genetic Algorithm for Feature Selection and Data Base Learning in Fuzzy-Rule Based Classification Systems(O. Cordon, F. Herrera, M.J. del Jesus, L. Magdalena, A.M. Sanchez, P. Villar).Mining Implication-Based Fuzzy Association Rules in Databases(E. Hullermeier, J. Beringer).Learning Graphical Models by Extending Optimal Spanning Trees(C. Borgelt, R. Kruse).Clustering Belief Functions Based on Attracting and ConflictingMetalevel Evidence(J. Schubert).FoundationsModels and Submodels of Fuzzy Theories(V. Novak).Numerical Representations of Fuzzy Relational Systems(S. Ovchinnikov).Normal Forms for Fuzzy Relations and Their Contribution to Universal Approximation(I. Perfilieva).Associative Operators Based on t-Norms and t-Conorms(M. Mas, R. Mesiar, M. Monserrat, J. Torrens).ApplicationsNon-Analytical Approaches to Model-Based Fault Detection and Isolation(P.M. Frank).A Hybrid Fuzzy-Fractal Approach for Time Series Analysis and Prediction and its Applications to Plant Monitoring(O. Castillo, P. Melin).Linguistic Modeling of Physical Task Characteristics(S. Visa, A. Ralescu, S. Yeung, A. Genaidy).Validation of Diagnostic Models Using Graphical Belief Networks(O. Kipersztok, H. Wang).Adjustment of Parallel Queuing Processes by Multi-Agent Control(R. Palm, T.A. Runkler).Is she gonna like it? Automated Inspection System Using Fuzzy Aggregation(A. Soria-Frisch, M. Koeppen, Th. Sy).Author Index

Additional information

NPB9780444513793
9780444513793
0444513795
Intelligent Systems for Information Processing: From Representation to Applications by B. Bouchon-Meunier (CNRS-UPMC, Paris, France)
New
Hardback
Elsevier Science & Technology
2003-11-07
488
N/A
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