Real World Data Mining Applications

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IntroductionMahmoud Abou-Nasr, Stefan Lessmann. Robert Stahlbock, Gary M. Weiss What Data Scientists can Learn from HistoryAaron Lai On Line Mining of Cyclic Association Rules From Parallel Dimension HierarchiesEya Ben Ahmed, Ahlem Nabli, Faıez Gargouri PROFIT: A Projected Clustering TechniqueDharmveer Singh Rajput, Pramod Kumar Singh, Mahua Bhattacharya Multi-Label Classification with a Constrained Minimum Cut ModelGuangzhi Qu, Ishwar Sethi, Craig Hartrick, Hui Zhang On the Selection of Dimension Reduction Techniques for Scientific ApplicationsYa Ju Fan, Chandrika Kamath Relearning Process for SPRT in Structural Change Detection of Time-Series DataRyosuke Saga, Naoki Kaisaku, Hiroshi Tsuji K-means clustering on a classifier-induced representation space: application to customer contact personalizationVincent Lemaire, Fabrice Clerot, Nicolas Creff Dimensionality Reduction using Graph Weighted Subspace Learning for Bankruptcy PredictionBernardete Ribeiro, Ning Chen Click Fraud Detection: Adversarial Pattern Recognition over 5 Years at MicrosoftBrendan 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 SubmissionKathryn Burn-Thornton, Tim Burman Data Mining Based Tax Audit Selection: A Case Study of a Pilot Project at the Minnesota Department of RevenueKuo-Wei Hsu, Nishith Pathak, Jaideep Srivastava, Greg Tschida, Eric Bjorklund A nearest neighbor approach to build a readable risk score forbreast cancerEmilien Gauthier, Laurent Brisson, Philippe Lenca, Stephane Ragusa Machine Learning for Medical Examination Report ProcessingYinghao Huang, Yi Lu Murphey, Naeem Seliya, Roy B. Friedenthal Data Mining Vortex Cores Concurrent with Computational Fluid Dynamics SimulationsClifton Mortensen, Steve Gorrell, Robert Woodley, Michael Gosnell A Data Mining Based Method for Discovery of Web Services and their CompositionsRichi Nayak, Aishwarya Bose Exploiting Terrain Information for Enhancing Fuel Economy of Cruising Vehicles by Supervised Training of Recurrent Neural OptimizersMahmoud 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 TechniquesCatherine Cheung, Julio J. Valdes, Matthew Li Multilayer Semantic Analysis In Image DatabasesIsmail El Sayad, Jean Martinet, Zhongfei (Mark) Zhang, Peter Eisert 

Data mining applications range from commercial to social domains, with novel applications appearing swiftly; for example, within the context of social networks. The expanding application sphere and social reach of advanced data mining raise pertinent issues of privacy and security. Present-day data mining is a progressive multidisciplinary endeavor. This inter- and multidisciplinary approach is well reflected within the field of information systems. The information systems research addresses software and hardware requirements for supporting computationally and data-intensive applications. Furthermore, it encompasses analyzing system and data aspects, and all manual or automated activities. In that respect, research at the interface of information systems and data mining has significant potential to produce actionable knowledge vital for corporate decision-making. The aim of the proposed volume is to provide a balanced treatment of the latest advances and developments in data mining; in particular, exploring synergies at the intersection with information systems. It will serve as a platform for academics and practitioners to highlight their recent achievements and reveal potential opportunities in the field. Thanks to its multidisciplinary nature, the volume is expected to become a vital resource for a broad readership ranging from students, throughout engineers and developers, to researchers and academics. 

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Mahmoud Abou-Nasr

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