Philip S. Yu, Yanchang Zhao, Graham Williams, Carlos Soares
DDDM: Domain Driven Data Mining
In the last decade, data mining has emerged as one of most vivacious areas in information technology.
Although many algorithms and techniques for data mining have been proposed, it still remains an open problem to successfully apply them to discover actionable knowledge in real-life applications in various domains.
The International Workshop on Domain Driven Data Mining (DDDM)
To provide a premier forum for sharing findings, knowledge, insight, experience and lessons in tackling potential challenges in discovering actionable knowledge from complex domain problems,
To promote the interaction of and bridge the gap between data mining research and business expectations, and
To drive a paradigm shift from traditional data-centered hidden pattern mining to domain-driven actionable knowledge discovery.
To design next-generation data mining methodology for actionable knowledge discovery and identify how KDD techniques can better contribute to critical domain problems in theory and practice;
To devise domain-driven data mining techniques to strengthen business intelligence in complex enterprise applications;
To present the applications of domain-driven data mining and demonstrate how KDD can be effectively deployed to solve complex practical problems; and
To identify challenges and future directions for data mining research and development in the dialogue between academia and industry.