Real World Data Mining Applications için kapak resmi
Real World Data Mining Applications
Başlık:
Real World Data Mining Applications
Yazar:
Abou-Nasr, Mahmoud. editor.
ISBN:
9783319078120
Fiziksel Niteleme:
XVI, 418 p. 144 illus., 96 illus. in color. online resource.
Seri:
Annals of Information Systems, 17
İçindekiler:
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.
Özet:
Introduction Mahmoud Abou-Nasr, Stefan Lessmann. Robert Stahlbock, Gary M. Weiss   What Data Scientists can Learn from History Aaron Lai   On Line Mining of Cyclic Association Rules From Parallel Dimension Hierarchies Eya Ben Ahmed, Ahlem Nabli, Faıez Gargouri   PROFIT: A Projected Clustering Technique Dharmveer Singh Rajput, Pramod Kumar Singh, Mahua Bhattacharya   Multi-Label Classification with a Constrained Minimum Cut Model Guangzhi Qu, Ishwar Sethi, Craig Hartrick, Hui Zhang   On the Selection of Dimension Reduction Techniques for Scientific Applications Ya Ju Fan, Chandrika Kamath   Relearning Process for SPRT in Structural Change Detection of Time-Series Data Ryosuke Saga, Naoki Kaisaku, Hiroshi Tsuji   K-means clustering on a classifier-induced representation space: application to customer contact personalization Vincent Lemaire, Fabrice Clerot, Nicolas Creff   Dimensionality Reduction using Graph Weighted Subspace Learning for Bankruptcy Prediction Bernardete Ribeiro, Ning Chen   Click Fraud Detection: Adversarial Pattern Recognition over 5 Years at Microsoft Brendan Kitts, Jing Ying Zhang, Gang Wu, Wesley Brandi, Julien Beasley, Kieran Morrill, John Ettedgui, Sid Siddhartha, Hong Yuan, Feng Gao, Peter Azo, Raj Mahato   A Novel Approach for Analysis of ’Real World’ Data: A Data Mining Engine for Identification of Multi-author Student Document Submission Kathryn Burn-Thornton, Tim Burman   Data Mining Based Tax Audit Selection: A Case Study of a Pilot Project at the Minnesota Department of Revenue Kuo-Wei Hsu, Nishith Pathak, Jaideep Srivastava, Greg Tschida, Eric Bjorklund   A nearest neighbor approach to build a readable risk score for breast cancer Emilien Gauthier, Laurent Brisson, Philippe Lenca, Stephane Ragusa   Machine Learning for Medical Examination Report Processing Yinghao Huang, Yi Lu Murphey, Naeem Seliya, Roy B. Friedenthal   Data Mining Vortex Cores Concurrent with Computational Fluid Dynamics Simulations Clifton Mortensen, Steve Gorrell, Robert Woodley, Michael Gosnell   A Data Mining Based Method for Discovery of Web Services and their Compositions Richi Nayak, Aishwarya Bose   Exploiting Terrain Information for Enhancing Fuel Economy of Cruising Vehicles by Supervised Training of Recurrent Neural Optimizers Mahmoud Abou-Nasr, John Michelini, Dimitar Filev   Exploration of Flight State and Control System Parameters for Prediction of Helicopter Loads via Gamma Test and Machine Learning Techniques Catherine Cheung, Julio J. Valdes, Matthew Li   Multilayer Semantic Analysis In Image Databases Ismail El Sayad, Jean Martinet, Zhongfei (Mark) Zhang, Peter Eisert  .