Advances in Intelligent Data Analysis XIV -

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Résumé :
This book constitutes the refereed conference proceedings of the 14th International Conference on Intelligent Data Analysis, which was held in October 2015 in?Saint ?tienne. France. The 29 revised full papers were carefully reviewed and selected from 65 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. To facilitate this, IDA 2015 will?feature two tracks: a regular Proceedings track, as well as a Horizon track?for early-stage research of potentially ground-breaking nature.

Sommaire:

Data analytics and optimization for assessing a ride sharing system.- Constraint-Based Querying for Bayesian Network Exploration.- Efficient Model Selection for Regularized Classification by Exploiting Unlabeled Data.- Segregation Discovery in a Social Network of Companies.- A first+-order-logic based model for grounded language learning.- A parallel distributed processing algorithm for image feature extraction.- Modeling concept drift: A probabilistic graphical model based approach.- Diversity-driven Widening of Hierarchical Agglomerative Clustering.- Batch Steepest-Descent-Mildest-Ascent for Interactive Maximum Margin Clustering.- Time Series Classification with Representation Ensembles.- Simultaneous Clustering and Model Selection for Multinomial Distribution: A Comparative Study.- On Binary Reduction of Large-scale Multiclass Classification Problems.- Probabilistic Active Learning in Data Streams.- Implicitly Constrained Semi-Supervised Least Squares Classification.- Diagonal Co-clustering Algorithm for Document-Word Partitioning.- I-Louvain: an attributed graph clustering method.- Class-based outlier detection: staying zombies or awaiting for resurrection?.- Using Metalearning for Prediction of Taxi Trip Duration Using Different Granularity Levels.- Using entropy as a measure of acceptance for multi-label classification.- Investigation of Node Deletion Techniques for Clustering Applications of Growing Self Organizing Maps.- Exploratory topic modeling with distributional semantics.- Assigning Geo-Relevance of Sentiments Mined from Location-Based Social Media Posts.- Continuous and Discrete Deep Classifiers for Data Integration.- A Bayesian Approach for Identifying Multivariate Differences Between Groups.- Automatically Discovering Offensive Patterns in Soccer Match Data.- Fast Algorithm Selection using Learning Curves.- Optimally Weighted Cluster Kriging for Big Data Regression.- Slower can be faster: The iRetis incremental model tree learner.- VoQs: A Web Application for Visualization of Questionnaire Surveys.