A survey of association rule mining in text applications

In data mining, association rule is an eminent research field to discover frequent pattern in data repositories of either real world datasets or synthetic datasets. As an association rule mining has confined in that every rule fulfilling a set of constraints such as minimum support and confidence. The objective of this survey is to discuss the basic techniques of association rule mining and text mining concepts. Also, the various transactions of text documents are available in different data warehouses. Particularly, this analysis is carried some of the text based medical applications. This work is specifies to integrate one of the association rule mining algorithm namely Apriori into text mining in order to find interesting patterns and it can easily understand by visualization techniques.