Advances in Intelligent Data Analysis XVI de Niall Adams

Advances in Intelligent Data Analysis XVI: 16th International Symposium, IDA 2017, London, UK, October 26–28, 2017, Proceedings: Lecture Notes in Computer Science, cartea 10584

Niall Adams

Allan Tucker

David Weston

This book constitutes the conference proceedings of the 16th International Symposium on Intelligent Data Analysis, which was held in October 2017 in London, UK.

The 28 full papers presented in this book were carefully reviewed and selected from 66 submissions. The traditional focus of the IDA symposium series is on end-to-end intelligent support for data analysis. IDA solicits papers on all aspects of intelligent data analysis, including papers on intelligent support for modelling and analyzing data from complex, dynamical systems.

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Cuprins

Improving Chairlift Security with Deep Learning.- Discovering motifs with variants in music databases.- Biclustering Multivariate Time Series.- Visualization of Topic-Sentiment Dynamics in Crowdfunding Projects.- Regression tree for bandits models in A/B testing.- Seasonal Variation in Collective Mood via Twitter Content and Medical Purchases.- Skin Cancer Detection in Dermoscopy Images Using Sub-Region Features.- Bucket Selection: A Model-Independent Diverse Selection Strategy for Widening.- Interactive Pattern Sampling for Characterizing Unlabeled Data.- Searching for Spatio-Temporal-Keyword Patterns in Semantic Trajectories.- Natural Language Analysis of Online Health Forums.- Freudian Slips: Analysing the Internal Representations of a Neural Network from its Mistakes.- KAPMiner: Mining ordered association rules with constraints.- A Dynamic Adaptive Questionnaire for Improved Disease Diagnostics.- ABIDE: Querying Time-Evolving Sequences of Temporal Intervals.- The Actors of History:Narrative Network Analysis Reveals the Institutions of Power in British Society Between 1800-1950.- Learning DTW-Preserving Shapelets.- Droplet Ensemble Learning on Drifting Data Streams.- Predictive clustering trees for hierarchical multi-target regression.- Identifying novel features from specimen data for the prediction of valuable field trips.- Adapting supervised classifiation algorithms to arbitrary weak label scenarios.- The Combination of Decision in Crowds When The Number of Reliable Annotator is Rare.- Estimating Sequence Similarity from Contig Sets.- Computational Topology Techniques for Characterizing Time-Series Data.- Improving Cold-Start Recommendations with Social-Media Trends and Reputations.- Hierarchical Novelty Detection.- Towards automatic evaluation of asphalt irregularity using smartphone's Sensors.- A structural benchmark for logical argumentation frameworks.