Application of Association Rule Mining to Help Determine the Process of Career Selection

The enormous data present at a university can be analyzed to generate useful information regarding the career paths chosen by students over the last few years. This information can not only be used by the students for analyzing the scope of their chosen career path but also by various authorities in analyzing the present career trends and understanding the scope of improvement among the less chosen ones. Dynamic Itemset Counting algorithm is an Association Rule Mining Technique used to identify patterns from an enormous amount of data, such as the data present at a university’s repository. This model is an attempt towards uncovering hidden patterns. The generated results of the algorithm help in giving useful insights to decision makers in helping them make better and informed decisions.