Decision Tree based Routine Generation (DRG) algorithm: A data mining advancement to generate academic routine for open credit system

Abstract

Mining data from a database using classification algorithm is not an innovative technique. This paper presents a technique namely decision tree based routine generation (DRG) algorithm to create an academic routine. The concept of open credit course registration system (after completion of pre-requisite courses any student may choose any course in any semester) makes the research more challenging and complex to accomplish. This is an NP-hard problem and hence unsolvable to satisfy all students and teachers at the same time. A level of tolerance has to be added to make the evaluation efficient and effective to achieve the goal, a conflict free routine. OLAP representation helps to classify the courses along with the proposed algorithm to eliminate some constraints. Day-based pattern, minimum Manhattan distance between courses of same teacher, minimum conflicted course distribution has been stage-managed to classify the courses. To alleviate the algorithm, decision tree based models and sequential search methods are espoused with computational results.