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Modeling Decisions for Artificial Intelligence

Overview of attention for book
Cover of 'Modeling Decisions for Artificial Intelligence'

Table of Contents

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    Book Overview
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    Chapter 1 Provenance and Privacy
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    Chapter 2 Comparison of Risk Averse Utility Functions on Two-Dimensional Regions
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    Chapter 3 Symmetrization Methods for Aggregation Functions
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    Chapter 4 Event-Based Transformations of Capacities
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    Chapter 5 Pan-Integrals Based on Optimal Measures
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    Chapter 6 Orness and Cardinality Indices for Averaging Inclusion-Exclusion Integrals
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    Chapter 7 $$L_1$$ -space for Sugeno Integral
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    Chapter 8 An Adaptation of the ML-kNN Algorithm to Predict the Number of Classes in Hierarchical Multi-label Classification
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    Chapter 9 On Fuzzy Clustering for Categorical Multivariate Data Induced by Polya Mixture Models
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    Chapter 10 Comparison of Fuzzy Co-clustering Methods in Collaborative Filtering-Based Recommender System
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    Chapter 11 Differentially Private Data Sets Based on Microaggregation and Record Perturbation
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    Chapter 12 A Methodology to Compare Anonymization Methods Regarding Their Risk-Utility Trade-off
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    Chapter 13 Session-Based Network Intrusion Detection Using a Deep Learning Architecture
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    Chapter 14 A Hybrid Model of ARIMA and ANN with Discrete Wavelet Transform for Time Series Forecasting
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    Chapter 15 A Novel Hybrid Model for Activity Recognition
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    Chapter 16 Constructing Document Vectors Using Kernel Density Estimates
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    Chapter 17 On Cell Detection System with User Interaction
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    Chapter 18 A Fuzzy Colour Model Sensitive to the Context: Study Cases Using PRAGR and Logics
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    Chapter 19 Joint Subjective Opinions
Overall attention for this book and its chapters
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Mentioned by

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1 tweeter

Citations

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Readers on

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23 Mendeley
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Title
Modeling Decisions for Artificial Intelligence
Published by
Springer International Publishing, January 2017
DOI 10.1007/978-3-319-67422-3
ISBNs
978-3-31-967422-3, 978-3-31-967421-6
Editors

Vicenç Torra, Yasuo Narukawa, Aoi Honda, Sozo Inoue

View on publisher site
Twitter Demographics

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 17%
Researcher 3 13%
Professor 2 9%
Student > Ph. D. Student 2 9%
Unknown 12 52%
Readers by discipline Count As %
Computer Science 5 22%
Engineering 4 17%
Earth and Planetary Sciences 1 4%
Business, Management and Accounting 1 4%
Unknown 12 52%

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