An architecture for active DSS
Proceedings of the Twenty-First Annual Hawaii International Conference on Decision Support and Knowledge Based Systems Track
An active modeling system for econometric analysis
Decision Support Systems
GOST: an active modeling system for costing and planning NASA space programs
Journal of Management Information Systems
Generating optimization-based decision support systems
HICSS '95 Proceedings of the 28th Hawaii International Conference on System Sciences
Communications of the ACM - Services science
What academic research tells us about service
Communications of the ACM - Services science
Resource planning for business services
Communications of the ACM - Services science
Service systems, service scientists, SSME, and innovation
Communications of the ACM - Services science
Information Systems Research
TDML: A Data Mining Language for Transaction Databases
FSKD '07 Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 04
Design of Service Systems under Variability: Research Issues
HICSS '08 Proceedings of the Proceedings of the 41st Annual Hawaii International Conference on System Sciences
An XML-enabled data mining query language: XML-DMQL
International Journal of Business Intelligence and Data Mining
PMML in Action: Unleashing the Power of Open Standards for Data Mining and Predictive Analytics
PMML in Action: Unleashing the Power of Open Standards for Data Mining and Predictive Analytics
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Research into service provision and innovation is becoming progressively more important as automated service-provision via the web matures as a technology. We describe a web-based targeting platform that uses advanced dynamic model building techniques to conduct intelligent reporting and modeling. The impact of the automated targeting services is realized through a knowledge base that drives the development of predictive model(s). The knowledge base is comprised of a rules engine that guides and evaluates the development of an automated model-building process. The template defines the model classifier (e.g., logistic regression, multinomial logit, ordinary least squares, etc.) in concert with rules for data filling and transformations. Additionally, the template also defines which variables to test ("include" rules) and which variables to retain ("keep" rules). The "final" model emerges from the iterative steps undertaken by the rules engine, and is utilized to target, or rank, the best prospects. This automated modeling approach is designed to cost-effectively assist businesses in their targeting activities--independent of the firm's size and targeting needs. We describe how the service has been utilized to provide "targeting services" for a small to medium business direct marketing campaign, and for direct sales-force targeting in a larger firm. Empirical results suggest that the automated modeling approach provides superior "service" in terms of cost and timing compared to more traditional manual service provision.