Discovering Temporal Relation Rules Mining from Interval Data

In this paper, we propose a new data mining technique that can address the temporal relation rules of temporal interval data by using Allen’s theory. We present two new algorithms for discovering temporal relationships: one is to preprocess an algorithm for the generalization of temporal interval data and to transform timestamp data into temporal interval data; and the other is to use a temporal relation algorithm for mining temporal relation rules and to discover the rules from temporal interval data. This technique can provide more useful knowledge in comparison with other conventional data mining techniques.