Advances in Intelligent Data Analysis XVII 17th International Symposium, IDA 2018, 's-Hertogenbosch, The Netherlands, October 24-26, 2018, Proceedings /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Duivesteijn, Wouter (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Siebes, Arno (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Ukkonen, Antti (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Έκδοση: 1st ed. 2018.
• Σειρά: Information Systems and Applications, incl. Internet/Web, and HCI ; 11191
• Θέματα: Database management.; Artificial intelligence.; Computers.; Application software.; Database Management.; Artificial Intelligence.; Information Systems and Communication Service.; Computer Applications.

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 2...

Πίνακας περιεχομένων:

• 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.