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Advances in Intelligent Data Analysis XVII

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Cover of 'Advances in Intelligent Data Analysis XVII'

Table of Contents

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    Book Overview
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    Chapter 1 Elements of an Automatic Data Scientist
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    Chapter 2 The Need for Interpretability Biases
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    Chapter 3 Open Data Science
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    Chapter 4 Automatic POI Matching Using an Outlier Detection Based Approach
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    Chapter 5 Fact Checking from Natural Text with Probabilistic Soft Logic
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    Chapter 6 ConvoMap: Using Convolution to Order Boolean Data
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    Chapter 7 Training Neural Networks to Distinguish Craving Smokers, Non-craving Smokers, and Non-smokers
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    Chapter 8 Missing Data Imputation via Denoising Autoencoders: The Untold Story
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    Chapter 9 Online Non-linear Gradient Boosting in Multi-latent Spaces
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    Chapter 10 MDP-based Itinerary Recommendation using Geo-Tagged Social Media
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    Chapter 11 Multiview Learning of Weighted Majority Vote by Bregman Divergence Minimization
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    Chapter 12 Non-negative Local Sparse Coding for Subspace Clustering
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    Chapter 13 Pushing the Envelope in Overlapping Communities Detection
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    Chapter 14 Right for the Right Reason: Training Agnostic Networks
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    Chapter 15 Link Prediction in Multi-layer Networks and Its Application to Drug Design
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    Chapter 16 A Hierarchical Ornstein-Uhlenbeck Model for Stochastic Time Series Analysis
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    Chapter 17 Analysing the Footprint of Classifiers in Overlapped and Imbalanced Contexts
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    Chapter 18 Tree-Based Cost Sensitive Methods for Fraud Detection in Imbalanced Data
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    Chapter 19 Reduction Stumps for Multi-class Classification
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    Chapter 20 Decomposition of Quantitative Gaifman Graphs as a Data Analysis Tool
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    Chapter 21 Exploring the Effects of Data Distribution in Missing Data Imputation
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    Chapter 22 Communication-Free Widened Learning of Bayesian Network Classifiers Using Hashed Fiedler Vectors
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    Chapter 23 Expert Finding in Citizen Science Platform for Biodiversity Monitoring via Weighted PageRank Algorithm
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    Chapter 24 Random Forests with Latent Variables to Foster Feature Selection in the Context of Highly Correlated Variables. Illustration with a Bioinformatics Application.
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    Chapter 25 Don’t Rule Out Simple Models Prematurely: A Large Scale Benchmark Comparing Linear and Non-linear Classifiers in OpenML
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    Chapter 26 Detecting Shifts in Public Opinion: A Big Data Study of Global News Content
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    Chapter 27 Biased Embeddings from Wild Data: Measuring, Understanding and Removing
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    Chapter 28 Real-Time Excavation Detection at Construction Sites using Deep Learning
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    Chapter 29 COBRAS: Interactive Clustering with Pairwise Queries
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    Chapter 30 Automatically Wrangling Spreadsheets into Machine Learning Data Formats
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    Chapter 31 Learned Feature Generation for Molecules
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Mentioned by

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17 tweeters

Citations

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Readers on

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Title
Advances in Intelligent Data Analysis XVII
Published by
Springer International Publishing, December 2018
DOI 10.1007/978-3-030-01768-2
ISBNs
978-3-03-001767-5, 978-3-03-001768-2
Editors

Duivesteijn, Wouter, Siebes, Arno, Ukkonen, Antti

Twitter Demographics

The data shown below were collected from the profiles of 17 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 25%
Student > Ph. D. Student 2 17%
Researcher 2 17%
Student > Bachelor 1 8%
Student > Postgraduate 1 8%
Other 0 0%
Unknown 3 25%
Readers by discipline Count As %
Computer Science 7 58%
Engineering 2 17%
Unknown 3 25%