Finding Association Rules in College Course Progression

Abstract

Association Rules are a data mining technique that aims at finding patterns in data that explain how different elements of the data influence each other. In this project this technique is used to find associations that describe the trends of college course completions and results. This project used a dataset from the University of Évora for rule finding. This paper shows how the dataset had to be preprocessed first in order to be mined, and describes the techniques and algorithms used.