Real world data mining applications / edited by Mahmoud Abou-Nasr, Stefan Lessmann, Robert Stahlbock, Gary M. Weiss.

Springer eBooks

Introduction -- What Data Scientists can Learn from History -- On Line Mining of Cyclic Association Rules From Parallel Dimension Hierarchies -- PROFIT: A Projected Clustering Technique -- Multi-Label Classification with a Constrained Minimum Cut Model -- On the Selection of Dimension Reduction Techniques for Scientific Applications -- Relearning Process for SPRT In Structural Change Detection of Time-Series Data -- K-means clustering on a classifier-induced representation space: application to customer contact personalization -- Dimensionality Reduction using Graph Weighted Subspace Learning for Bankruptcy Prediction -- Click Fraud Detection: Adversarial Pattern Recognition over 5 years at Microsoft -- A Novel Approach for Analysis of 'Real World' Data: A Data Mining Engine for Identification of Multi-author Student Document Submission -- Data Mining Based Tax Audit Selection: A Case Study of a Pilot Project at the Minnesota Department of Revenue -- A nearest neighbor approach to build a readable risk score for breast cancer -- Machine Learning for Medical Examination Report Processing -- Data Mining Vortex Cores Concurrent with Computational Fluid Dynamics Simulations -- A Data Mining Based Method for Discovery of Web Services and their Compositions -- Exploiting Terrain Information for Enhancing Fuel Economy of Cruising Vehicles by Supervised Training of Recurrent Neural Optimizers -- Exploration of Flight State and Control System Parameters for Prediction of Helicopter Loads via Gamma Test and Machine Learning Techniques -- Multilayer Semantic Analysis In Image Databases.

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