An overview of techniques in mining association rules

Association rule discovery is one of the most important techniques in the field of data mining. Key component of data mining is whether Knowledge Discovery or Knowledge Prediction, data mining takes information that was once quite difficult to detect and presents it in an easily understandable format (i.e. graphical or statistical). Advanced data mining methods rely on Relational Data, or data that can be stored and modeled easily through use of relational databases. It aims at finding interesting patterns among the databases. In data mining, association rule learning is a popular and well researched method for discovering interesting relations between variables in large databases. They are employed today in many application areas including web usage mining, intrusion detection and bioinformatics. The use of association rule mining technique is to describe the associations among items in a database and to identify domain knowledge hidden in large volume of data efficiently. This paper provides an overview of techniques that are used to improve the performance and efficiency of Association Rule Mining (ARM) from huge databases.