Use of Domain Knowledge for Fast Mining of Association Rules

Data Mining is often considered as a process of automatic discovery of new knowledge from large databases. However the role of the human within the discovery process is essential. Domain knowledge consists of information about the data that is made available by the domain experts. Such knowledge constrains the search space and enhances the performance of the mining process. We have developed an algorithm that makes use of domain knowledge for efficient mining of association rules from university course enrollment database. The experimental results show that the developed algorithm results in faster mining of association rules from the elective course university dataset as compared to mining the same patterns with an association rule-mining algorithm that does not makes use of domain knowledge.