Data Mining for Business Applications presents the state-of-the-art research and development outcomes on methodologies, techniques, approaches and successful applications in the area. The contributions mark a paradigm shift from adata-centered pattern mininga to adomain driven actionable knowledge discoverya for next-generation KDD research and applications. The contents identify how KDD techniques can better contribute to critical domain problems in theory and practice, and strengthen business intelligence in complex enterprise applications. The volume also explores challenges and directions for future research and development in the dialogue between academia and business.Break Point Analysis  monitors intra-account behaviour by detecting rapid weekly spending. A neural ... Ford Explorers with Firestone tires from a specific factory had tire-thread separation problem which resulted in 800 injuries. As thoseanbsp;...
|Title||:||Data Mining for Business Applications|
|Author||:||Longbing Cao, Philip S. Yu, Chengqi Zhang, Huaifeng Zhang|
|Publisher||:||Springer Science & Business Media - 2008-10-03|