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E-raamat: Advances in Intelligent Data Analysis XV: 15th International Symposium, IDA 2016, Stockholm, Sweden, October 13-15, 2016, Proceedings

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This book constitutes the refereed conference proceedings of the 15th International Conference on Intelligent Data Analysis, which was held in October 2016 in Stockholm, Sweden.
The 36 revised full papers presented were carefully reviewed and selected from 75 submissions. The traditional focus of the IDA symposium series is on end-to-end intelligent support for data analysis. The symposium aims to provide a forum for inspiring research contributions that might be considered preliminary in other leading conferences and journals, but that have a potentially dramatic impact. 

DSCo-NG: A Practical Language Modeling Approach for Time Series
Classification.- Ranking Accuracy for Logistic-GEE models.- The Morality
Machine: Tracking Moral Values in Tweets.- A Hybrid Approach for
Probabilistic Relational Models Structure Learning.- On the Impact of Data
Set Size in Transfer Learning Using Deep Neural Networks.- Obtaining Shape
Descriptors from a Concave Hull-Based Clustering Algorithm.- Visual
Perception of Discriminative Landmarks in Classified Time Series.- Spotting
the Diffusion of New Psychoactive Substances over the Internet.- Feature
Selection Issues in Long-Term Travel Time Prediction.- A Mean-Field
Variational Bayesian Approach to Detecting Overlapping Communities with Inner
Roles Using Poisson Link Generation.- Online Semi-supervised Learning for
Multi-target Regression in Data streams Using AMRules.- A Toolkit for
Analysis of Deep Learning Experiments.- The Optimistic Method for Model
Estimation.- Does Feature Selection Improve Classification? A Large Scale
Experiment in OpenML.- Learning from the News: Predicting Entity Popularity
on Twitter.- Multi-scale Kernel PCA and Its Application to Curvelet-based
Feature Extraction for Mammographic Mass Characterization.- Weakly-supervised
Symptom Recognition for Rare Diseases in Biomedical Text.- Estimating
Sequence Similarity from Read Sets for Clustering Sequencing Data.- Widened
Learning of Bayesian Network Classifiers.- Vote Buying Detection via
Independent Component Analysis.- Unsupervised Relation Extraction in
Specialized Corpora Using Sequence Mining.- A Framework for Interpolating
Scattered Data Using Space-filling Curves.- Privacy-Awareness of Distributed
Data Clustering Algorithms Revisited.- Bi-stochastic Matrix Approximation
Framework for Data Co-clustering.- Sequential Cost-Sensitive Feature
Acquisition.- Explainable and Efficient Link Prediction in Real-World Network
Data.- DGRMiner: Anomaly Detection and Explanation in Dynamic Graphs.-
Similarity Based Hierarchical Clustering with an Application to Text
Collections.- Determining Data Relevance Using Semantic Types and Graphical
Interpretation Cues.- A First Step Toward Quantifying the Climate's
Information Production over the Last 68,000 Years.- HAUCA Curves for the
Evaluation of Biomarker Pilot Studies with Small Sample Sizes and Large
Numbers of Features.- Stability Evaluation of Event Detection Techniques for
Twitter.- IDA 2016 Industrial Challenge: Using Machine Learning for
Predicting Failures.- An Optimized k-NN Approach for Classification on
Imbalanced Datasets with Missing Data.- Combining Boosted Trees with
Metafeature Engineering for Predictive Maintenance.- Prediction of Failures
in the Air Pressure System of Scania Trucks Using a Random Forest and Feature
Engineering.