Domain-Driven, Actionable Knowledge Discovery

Longbing Cao, Chengqi Zhang, Qiang Yang, David Bell, Michail Vlachos, Bahar Taneri, Eamonn Keogh, Philip S. Yu, Ning Zhong, Mafruz Zaman Ashrafi, David Taniar, Eugene Dubossarsky (+1 others)
2007 IEEE Intelligent Systems  
Data mining increasingly faces complex challenges in the real-life world of business problems and needs. 1 The gap between business expectations and R&D results in this area involves key aspects of the field, such as methodologies, targeted problems, pattern interestingness, and infrastructure support. Both researchers and practitioners are realizing the importance of domain knowledge to close this gap and develop actionable knowledge for real user needs.
doi:10.1109/mis.2007.67 fatcat:obiwzv5q55ctfgre4smnq73gum