Trends and Applications in Knowledge Discovery and Data Mining

Trends and Applications in Knowledge Discovery and Data Mining

PAKDD 2017 Workshops, MLSDA, BDM, DM-BPM Jeju, South Korea, May 23, 2017, Revised Selected Papers

Yu, Jeffrey Xu; Lim, Ee-Peng; Moon, Yang-Sae; Kang, U

Springer International Publishing AG

10/2017

203

Mole

Inglês

9783319672731

15 a 20 dias

3401

Descrição não disponível.
Early Classification of Multivariate Time Series on Distributed and In-Memory Platforms.- Behavior Classification of Dairy Cows fitted with GPS collars.- Dynamic Real-time Segmentation and Recongnition of Activities using a Multi-feature Windowing Approach.- Feature Extraction from EEG data for a P300 Based Brain-computer Interface.- Thermal Stratification Prediction at Lake Trevallyn.- Development of a Software Vulnerability Prediction Web Service based on Artificial Neural Networks .- Diversification Heuristics in Bees Swarm Optimization for Association Rules Mining.- Improved CFDP Algorithms Based on Shared Nearest Neighbors and Transitive Closure.- CNN-based Sequence Labeling for Fine-grained Opinion Mining of Microblogs.- A Genetic Algorithm for Interpretable Model Extraction from Decision Tree Ensembles.- Self-Adaptive Weighted Extreme Learning Machine for Imbalanced Classification Problems.- Estimating Word Probabilities with Neural Networks in Latent Dirichlet Allocation.- GA-Apriori: Combining Apriori Heuristic and Genetic Algorithms for Solving the Frequent Itemsets Mining Problem.- Shelf Time Analysis in CTP Insurance Claims Processing.- Automated Product-Attribute Mapping.- A Novel Extreme Learning Machine-based Classification Algorithm for Uncertain Data.- SPGLAD: A Self-Paced Learning-based Crowdsourcing Classification Model.
Machine learning theory;Machine learning;Classification and regression tree;Unsupervised learning;Computational biology;Biology-related information processing;Systems biology;Business intelligence;Business process management;Feature extraction and selection