Mining association rules of quantitative movement pattern in databases

We present a new form of association rules to deal with quantitative attributes in time series databases. This kind of rules, called an association rules of quantitative movement pattern (AR-QMP), can represent relations of movement patterns about quantitative attributes. We first analyze the necessity of new association rules. Next, we design a model to describe the movement pattern and present implementation strategies based on this model. Finally, we propose further work to discover predictive association rules about movement patterns