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Discovery Science

Overview of attention for book
Cover of 'Discovery Science'

Table of Contents

  1. Altmetric Badge
    Book Overview
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    Chapter 1 Evaluating Decision Makers over Selectively Labelled Data: A Causal Modelling Approach
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    Chapter 2 Mitigating Discrimination in Clinical Machine Learning Decision Support Using Algorithmic Processing Techniques
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    Chapter 3 WeakAL : Combining Active Learning and Weak Supervision
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    Chapter 4 Constrained Clustering via Post-processing
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    Chapter 5 Deep Convolutional Embedding for Painting Clustering: Case Study on Picasso’s Artworks
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    Chapter 6 Dynamic Incremental Semi-supervised Fuzzy Clustering for Bipolar Disorder Episode Prediction
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    Chapter 7 Iterative Multi-mode Discretization: Applications to Co-clustering
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    Chapter 8 COVID-19 Therapy Target Discovery with Context-Aware Literature Mining
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    Chapter 9 Semantic Annotation of Predictive Modelling Experiments
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    Chapter 10 Semantic Description of Data Mining Datasets: An Ontology-Based Annotation Schema
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    Chapter 11 $$\mathsf {FABBOO}$$ - Online Fairness-Aware Learning Under Class Imbalance
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    Chapter 12 FEAT: A Fairness-Enhancing and Concept-Adapting Decision Tree Classifier
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    Chapter 13 Unsupervised Concept Drift Detection Using a Student–Teacher Approach
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    Chapter 14 Assembled Feature Selection for Credit Scoring in Microfinance with Non-traditional Features
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    Chapter 15 Learning Surrogates of a Radiative Transfer Model for the Sentinel 5P Satellite
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    Chapter 16 Nets Versus Trees for Feature Ranking and Gene Network Inference
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    Chapter 17 Pathway Activity Score Learning for Dimensionality Reduction of Gene Expression Data
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    Chapter 18 Balancing Between Scalability and Accuracy in Time-Series Classification for Stream and Batch Settings
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    Chapter 19 DeCStor: A Framework for Privately and Securely Sharing Files Using a Public Blockchain
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    Chapter 20 Investigating Parallelization of MAML
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    Chapter 21 Extreme Algorithm Selection with Dyadic Feature Representation
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    Chapter 22 Federated Ensemble Regression Using Classification
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    Chapter 23 One-Class Ensembles for Rare Genomic Sequences Identification
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    Chapter 24 Explaining Sentiment Classification with Synthetic Exemplars and Counter-Exemplars
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    Chapter 25 Generating Explainable and Effective Data Descriptors Using Relational Learning: Application to Cancer Biology
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    Chapter 26 Interpretable Machine Learning with Bitonic Generalized Additive Models and Automatic Feature Construction
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    Chapter 27 Predicting and Explaining Privacy Risk Exposure in Mobility Data
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    Chapter 28 Maximizing Network Coverage Under the Presence of Time Constraint by Injecting Most Effective k-Links
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    Chapter 29 On the Utilization of Structural and Textual Information of a Scientific Knowledge Graph to Discover Future Research Collaborations: A Link Prediction Perspective
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    Chapter 30 Simultaneous Process Drift Detection and Characterization with Pattern-Based Change Detectors
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    Chapter 31 Extreme Gradient Boosted Multi-label Trees for Dynamic Classifier Chains
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    Chapter 32 Hierarchy Decomposition Pipeline: A Toolbox for Comparison of Model Induction Algorithms on Hierarchical Multi-label Classification Problems
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    Chapter 33 Missing Value Imputation with MERCS: A Faster Alternative to MissForest
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    Chapter 34 Multi-directional Rule Set Learning
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    Chapter 35 On Aggregation in Ensembles of Multilabel Classifiers
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    Chapter 36 Attention in Recurrent Neural Networks for Energy Disaggregation
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    Chapter 37 Enhanced Food Safety Through Deep Learning for Food Recalls Prediction
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    Chapter 38 FairNN  - Conjoint Learning of Fair Representations for Fair Decisions
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    Chapter 39 Improving Deep Unsupervised Anomaly Detection by Exploiting VAE Latent Space Distribution
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    Chapter 40 Detecting Temporal Anomalies in Business Processes Using Distance-Based Methods
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    Chapter 41 Mining Constrained Regions of Interest: An Optimization Approach
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    Chapter 42 Mining Disjoint Sequential Pattern Pairs from Tourist Trajectory Data
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    Chapter 43 Predicting the Health Condition of mHealth App Users with Large Differences in the Number of Recorded Observations - Where to Learn from?
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    Chapter 44 Spatiotemporal Traffic Anomaly Detection on Urban Road Network Using Tensor Decomposition Method
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    Chapter 45 Time Series Regression in Professional Road Cycling
Attention for Chapter 27: Predicting and Explaining Privacy Risk Exposure in Mobility Data
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Chapter title
Predicting and Explaining Privacy Risk Exposure in Mobility Data
Chapter number 27
Book title
Discovery Science
Published by
Springer, Cham, October 2020
DOI 10.1007/978-3-030-61527-7_27
Book ISBNs
978-3-03-061526-0, 978-3-03-061527-7
Authors

Francesca Naretto, Roberto Pellungrini, Anna Monreale, Franco Maria Nardini, Mirco Musolesi, Naretto, F, Pellungrini, R, Monreale, A, Nardini, FM, Musolesi, M, Naretto, Francesca, Pellungrini, Roberto, Monreale, Anna, Nardini, Franco Maria, Musolesi, Mirco

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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 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 1 14%
Student > Ph. D. Student 1 14%
Researcher 1 14%
Other 1 14%
Student > Postgraduate 1 14%
Other 0 0%
Unknown 2 29%
Readers by discipline Count As %
Computer Science 5 71%
Decision Sciences 1 14%
Unknown 1 14%

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