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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
  2. Altmetric Badge
    Chapter 1 A Characterization of Belief Merging Operators in the Regular Horn Fragment of Signed Logic
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    Chapter 2 Bivariate Risk Measures and Stochastic Orders
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    Chapter 3 Stochastic Orders on Two-Dimensional Space: Application to Cross Entropy
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    Chapter 4 Modeling Decisions in AI: Re-thinking Linda in Terms of Coherent Lower and Upper Conditional Previsions
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    Chapter 5 Ensemble Learning, Social Choice and Collective Intelligence
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    Chapter 6 An Unsupervised Capacity Identification Approach Based on Sobol’ Indices
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    Chapter 7 Probabilistic Measures and Integrals: How to Aggregate Imprecise Data
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    Chapter 8 Distorted Probabilities and Bayesian Confirmation Measures
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    Chapter 9 Constructive k-Additive Measure and Decreasing Convergence Theorems
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    Chapter 10 Generalization Property of Fuzzy Classification Function for Tsallis Entropy-Regularization of Bezdek-Type Fuzzy C-Means Clustering
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    Chapter 11 Nonparametric Bayesian Nonnegative Matrix Factorization
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    Chapter 12 SentiRank : A System to Integrate Aspect-Based Sentiment Analysis and Multi-criteria Decision Support
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    Chapter 13 Efficient Detection of Byzantine Attacks in Federated Learning Using Last Layer Biases
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    Chapter 14 Multi-object Tracking Combines Motion and Visual Information
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    Chapter 15 Classifying Candidate Axioms via Dimensionality Reduction Techniques
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    Chapter 16 Sampling Unknown Decision Functions to Build Classifier Copies
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    Chapter 17 Towards Analogy-Based Explanations in Machine Learning
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    Chapter 18 An Improved Bi-level Multi-objective Evolutionary Algorithm for the Production-Distribution Planning System
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    Chapter 19 Modifying the Symbolic Aggregate Approximation Method to Capture Segment Trend Information
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    Chapter 20 Efficiently Mining Gapped and Window Constraint Frequent Sequential Patterns
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    Chapter 21 Aggregating News Reporting Sentiment by Means of Hesitant Linguistic Terms
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    Chapter 22 Decision Trees as a Tool for Data Analysis. Elections in Barcelona: A Case Study
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    Chapter 23 Explaining Misclassification and Attacks in Deep Learning via Random Forests
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    Chapter 24 Fair-MDAV: An Algorithm for Fair Privacy by Microaggregation
Attention for Chapter 19: Modifying the Symbolic Aggregate Approximation Method to Capture Segment Trend Information
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  • Good Attention Score compared to outputs of the same age and source (76th percentile)

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Chapter title
Modifying the Symbolic Aggregate Approximation Method to Capture Segment Trend Information
Chapter number 19
Book title
Modeling Decisions for Artificial Intelligence
Published in
arXiv, September 2020
DOI 10.1007/978-3-030-57524-3_19
Book ISBNs
978-3-03-057523-6, 978-3-03-057524-3
Authors

Muhammad Marwan Muhammad Fuad, Muhammad Fuad, Muhammad Marwan

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users 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 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 1 33%
Unknown 2 67%
Readers by discipline Count As %
Computer Science 1 33%
Unknown 2 67%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 October 2020.
All research outputs
#14,671,229
of 24,998,746 outputs
Outputs from arXiv
#219,886
of 1,020,408 outputs
Outputs of similar age
#203,029
of 405,964 outputs
Outputs of similar age from arXiv
#6,793
of 31,380 outputs
Altmetric has tracked 24,998,746 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,020,408 research outputs from this source. They receive a mean Attention Score of 4.1. This one has done well, scoring higher than 76% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 405,964 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 31,380 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.