(Ebook) Intelligent Systems for Information Processing From Representation to Applications 1st Edition by B Bouchon Meunier, L Foulloy, Ronald R Yager ISBN 0444513795 9780080525655

(Ebook) Intelligent Systems for Information Processing From Representation to Applications 1st Edition by B Bouchon Meunier, L Foulloy, Ronald R Yager ISBN 0444513795 9780080525655

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ISBN 10: 0444513795 
ISBN 13: 9780080525655
Author: B Bouchon Meunier, L Foulloy, Ronald R Yager

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.

(Ebook) Intelligent Systems for Information Processing From Representation to Applications 1st Table of contents:

Part 1: Perception-based Information Processing

• Chapter 1: Toward a Perception-Based Theory of Probabilistic Reasoning with Imprecise Probabilities

Part 2: Representing Knowledge

• Chapter 2: Rough Set Uncertainty in an Object Oriented Data Model

• Chapter 3: On the Representation of Fuzzy Spatial Relations in Robot Maps

• Chapter 4: Fuzzy "Between" Operators in the Framework of Fuzzy Orderings

• Chapter 5: A Step towards Conceptually Improving Takagi-Sugeno's Approximation

• Chapter 6: Combining Heterogeneous Information in Group Decision Making

• Chapter 7: Function Approximation by Fuzzy Rough Sets

Part 3: Retrieving Information

• Chapter 8: Query Aggregation Reflecting Domain-knowledge

• Chapter 9: Modelling of Fuzzy and Uncertain Spatio-Temporal Information in Databases: A Constraint-based Approach

• Chapter 10: A General Framework for Meta-search based on Query-weighting and Numerical Aggregation Operators

• Chapter 11: On the Comparison of Aggregates over Fuzzy Sets

• Chapter 12: Towards an Intelligent Text Categorization for Web Resources: An Implementation

Part 4: Reasoning

• Chapter 13: Prototype Based Reasoning and Fuzzy Modeling

• Chapter 14: Gradual Handling of Contradiction in Argumentation Frameworks

• Chapter 15: Coherent Conditional Probability as a Tool for Default Reasoning

• Chapter 16: Detecting Conflict-Free Assumption-Based Knowledge Bases

Part 5: Uncertainty

• Chapter 17: Theory of Belief Functions: History and Prospects

• Chapter 18: Towards Another Logical Interpretation of Theory of Evidence and a New Combination Rule

• Chapter 19: Uncertainty, Type-2 Fuzzy Sets, and Footprints of Uncertainty

• Chapter 20: Rough Sets, Bayes' Theorem and Flow Graphs

• Chapter 21: Belief Revision as Combinatorial Optimization

• Chapter 22: Showing why Measures of Quantified Beliefs are Belief Functions

• Chapter 23: Extension of Coherent Lower Previsions to Unbounded Random Variables

Part 6: Learning and Mining

• Chapter 24: Clustering of Proximity Data using Belief Functions

• Chapter 25: A Hierarchical Linguistic Clustering Algorithm for Prototype Induction

• Chapter 26: A Multiobjective Genetic Algorithm for Feature Selection and Database Learning in Fuzzy Environments

• Chapter 27: Mining Implication-Based Fuzzy Association Rules in Databases

• Chapter 28: Learning Graphical Models by Extending Optimal Spanning Trees

• Chapter 29: Clustering Belief Functions Based on Attracting and Conflicting Metalevel Evidence

Part 7: Foundations

• Chapter 30: Models and Submodels of Fuzzy Theories

• Chapter 31: Numerical Representations of Fuzzy Relational Systems

• Chapter 32: Normal Forms for Fuzzy Relations and Their Contribution to Universal Approximation

• Chapter 33: Associative Operators Based on t-Norms and t-Conorms

Part 8: Applications

• Chapter 34: Non-Analytical Approaches to Model-Based Fault Detection and Isolation

• Chapter 35: A Hybrid Fuzzy-Fractal Approach for Time Series Analysis and Prediction and its Applications

• Chapter 36: Linguistic Modeling of Physical Task Characteristics

• Chapter 37: Validation of Diagnostic Models Using Graphical Belief Networks

• Chapter 38: Adjustment of Parallel Queuing Processes by Multi-Agent Control

• Chapter 39: Is She Gonna Like It? Automated Inspection System Using Fuzzy Aggregation

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