Advances in Intelligent Data Analysis XVII : 17th International Symposium, IDA 2018, 's-Hertogenbosch, The Netherlands, October 24-26, 2018, Proceedings / edited by Wouter Duivesteijn, Arno Siebes, Antti Ukkonen.

Cham : Springer International Publishing : Imprint: Springer, 2018.
1 online resource (XIII, 394 pages) : 133 illustrations
1st ed. 2018.
Computer Science (Springer-11645)
LNCS sublibrary. Information systems and applications, incl. Internet/Web, and HCI SL 3, 11191
Information Systems and Applications, incl. Internet/Web, and HCI ; 11191
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This book constitutes the conference proceedings of the 17th International Symposium on Intelligent Data Analysis, which was held in October 2018 in 's-Hertogenbosch, the Netherlands. The traditional focus of the IDA symposium series is on end-to-end intelligent support for data analysis. The 29 full papers presented in this book were carefully reviewed and selected from 65 submissions. The papers cover all aspects of intelligent data analysis, including papers on intelligent support for modeling and analyzing data from complex, dynamical systems.
Elements of an Automatic Data Scientist
The Need for Interpretability Biases Open Data Science
Automatic POI Matching Using an Outlier Detection Based Approach
Fact Checking from Natural Text with Probabilistic Soft Logic
ConvoMap: Using Convolution to Order Boolean Data
Training Neural Networks to distinguish craving smokers, non-craving smokers, and non-smokers
Missing Data Imputation via Denoising Autoencoders: the untold story
Online Non-Linear Gradient Boosting in Multi-Latent Spaces
MDP-based Itinerary Recommendation using Geo-Tagged Social Media
Multiview Learning of Weighted Majority Vote by Bregman Divergence Minimization
Non-Negative Local Sparse Coding for Subspace Clustering
Pushing the Envelope in Overlapping Communities Detection.-Right for the Right Reason: Training Agnostic Networks
Link Prediction in Multi-Layer Networks and its Application to Drug Design
A hierarchical Ornstein-Uhlenbeck model for stochastic time series analysis
Analysing the footprint of classi_ers in overlapped and imbalanced contexts
Tree-based Cost Sensitive Methods for Fraud Detection in Imbalanced Data
Reduction Stumps for Multi-Class Classification
Decomposition of quantitative Gaifman graphs as a data analysis tool
Exploring the Effects of Data Distribution in Missing Data Imputation
Communication-free Widened Learning of Bayesian Network Classifiers Using Hashed Fiedler Vectors
Expert finding in Citizen Science platform for biodiversity monitoring via weighted PageRank algorithm
Random forests with latent variables to foster feature selection in the context of highly correlated variables. Illustration with a bioinformatics application.-Don't Rule Out Simple Models Prematurely: a Large Scale Benchmark Comparing Linear and Non-linear Classifiers in OpenML
Detecting Shifts in Public Opinion: a big data study of global news content
Biased Embeddings from Wild Data: Measuring, Understanding and Removing
Real-Time Excavation Detection at Construction Sites using Deep Learning
COBRAS: Interactive Clustering with Pairwise Queries
Automatically Wrangling Spreadsheets into Machine Learning Data Formats
Learned Feature Generation for Molecules.
Duivesteijn, Wouter, editor., Editor,
Siebes, Arno. editor., Editor,
Ukkonen, Antti, editor., Editor,
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