Advances in Intelligent Data Analysis XV

15th International Symposium, IDA 2016, Stockholm, Sweden, October 13-15, 2016, Proceedings

Häftad, Engelska, 2016

AvHenrik Boström,Arno Knobbe,Carlos Soares,Panagiotis Papapetrou,Henrik Bostrom

719 kr

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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 traditional focus of the IDA symposium series is on end-to-end intelligent support for data analysis.

Produktinformation

Utgivningsdatum2016-09-21
Mått155 x 235 x 23 mm
Vikt633 g
FormatHäftad
SpråkEngelska
SerieLecture Notes in Computer Science
Antal sidor404
FörlagSpringer International Publishing AG
ISBN9783319463483

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Programmeringsböcker inom Data och it
Artificiell intelligens inom Data och it
Databaser inom Data och it
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Systemvetenskap och AI inom Data och it

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.