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Modeling Decisions for Artificial Intelligence

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Cover of 'Modeling Decisions for Artificial Intelligence'

Table of Contents

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    Book Overview
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    Chapter 1 An Overview of Hierarchical and Non-hierarchical Algorithms of Clustering for Semi-supervised Classification
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    Chapter 2 Fuzzy Programming Approaches to Robust Optimization
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    Chapter 3 Do We Know How to Integrate?
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    Chapter 4 Combination and Soft-Normalization of Belief Functions on MV-Algebras
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    Chapter 5 Using Linear Programming for Weights Identification of Generalized Bonferroni Means in R
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    Chapter 6 An Ordered Weighted Average with a Truncation Weight on Intervals
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    Chapter 7 Choquet Integral on the Real Line as a Generalization of the OWA Operator
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    Chapter 8 On WOWA Rank Reversal
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    Chapter 9 Extending Concordance and Discordance Relations to Hierarchical Sets of Criteria in ELECTRE-III Method
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    Chapter 10 An Extended LibQUAL+ Model Based on Fuzzy Linguistic Information
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    Chapter 11 Measure of Inconsistency for the Potential Method
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    Chapter 12 Hierarchical Bipolar Sugeno Integral Can Be Represented as Hierarchical Bipolar Choquet Integral
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    Chapter 13 Qualitative Integrals and Desintegrals – Towards a Logical View
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    Chapter 14 A Quantile Approach to Integration with Respect to Non-additive Measures
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    Chapter 15 Analysis of On-Line Social Networks Represented as Graphs – Extraction of an Approximation of Community Structure Using Sampling
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    Chapter 16 Using Profiling Techniques to Protect the User’s Privacy in Twitter
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    Chapter 17 Detecting Sensitive Information from Textual Documents: An Information-Theoretic Approach
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    Chapter 18 A Study of Anomaly Detection in Data from Urban Sensor Networks
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    Chapter 19 Comparing Random-Based and k -Anonymity-Based Algorithms for Graph Anonymization
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    Chapter 20 Heuristic Supervised Approach for Record Linkage
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    Chapter 21 Sampling Attack against Active Learning in Adversarial Environment
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    Chapter 22 Dynamic Credit-Card Fraud Profiling
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    Chapter 23 Representing Fuzzy Logic Programs by Graded Attribute Implications
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    Chapter 24 Refining Discretizations of Continuous-Valued Attributes
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    Chapter 25 Linear Programming with Graded Ill-Known Sets
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    Chapter 26 Sharing Online Cultural Experiences: An Argument-Based Approach
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    Chapter 27 Simple Proof of Basic Theorem for General Concept Lattices by Cartesian Representation
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    Chapter 28 On Some Properties of the Negative Transitivity Obtained from Transitivity
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    Chapter 29 Multi Criteria Operators for Multi-attribute Auctions
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    Chapter 30 Finding Patterns in Large Star Schemas at the Right Aggregation Level
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    Chapter 31 Application of Quantitative MCDA Methods for Parameter Setting Support of an Image Processing System
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    Chapter 32 Inductive Clustering and Twofold Approximations in Nearest Neighbor Clustering
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    Chapter 33 Marginality: A Numerical Mapping for Enhanced Exploitation of Taxonomic Attributes
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    Chapter 34 Introducing Incomparability in Modeling Qualitative Belief Functions
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    Chapter 35 On Rough Set Based Non Metric Model
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    Chapter 36 An Efficient Reasoning Method for Dependencies over Similarity and Ordinal Data
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Title
Modeling Decisions for Artificial Intelligence
Published by
Springer Berlin Heidelberg, November 2012
DOI 10.1007/978-3-642-34620-0
ISBNs
978-3-64-234619-4, 978-3-64-234620-0
Editors

Torra, Vicenç, Narukawa, Yasuo, López, Beatriz, Villaret, Mateu

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 25%
Unknown 3 75%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 75%
Student > Postgraduate 1 25%
Student > Master 1 25%
Student > Doctoral Student 1 25%
Unspecified 1 25%
Other 0 0%
Readers by discipline Count As %
Computer Science 5 125%
Business, Management and Accounting 1 25%
Unspecified 1 25%