Operations Research in Data Mining

Abstract

Data mining (DM) and operations research (OR) are two largely independent paradigms of science. DM involves data driven methods that are aimed at extracting meaningful patterns from data instances, whereas OR employs mathematical models and analytical techniques to achieve optimal solutions for complex decision‐making problems. DM and OR are also two overlapping disciplines. There is a growing interest in applying OR techniques to determine the optimal underlying fitting data structures in DM problems. This article provides a description of the basic concepts and methodologies of influential DM techniques, and discusses how OR can be applied to these techniques.

Monitoring of Operational Logistic Processes in General Cargo Warehouses Using Predictive Analysis

“…When creating the model, a so-called score function is used to evaluate how well the currently set parameters produce the training data. The process is called scoring in scientific literature [20]. The application of new, unknown data to the model generated by data mining is also called scoring [14].…”