Constraint based pattern mining and association rules are used in many applications like genetic sequence analysis, in finance for bankrupting prediction, in securities for fraud detection, in agriculture for discovering classification of plants etc. to get the user interesting knowledge. Constraints are useful to eliminate unwanted rules and also solves rule explosion problem. Many algorithms are proposed for constraint based pattern mining and association rule generation. These constraints are in the form of attribute, item length, time or duration, regular expression etc. Pushing constraints in a mining process gives user interesting discovery. Literature survey shows that performance of an algorithm improves with application of constraint during the mining process. The paper elaborates about the literature survey on use of constraints in generation of association rules with different categories of constraints with its properties.

constraint;frequent;sequence;pattern;mining

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