Finding Localized Associations in Market Basket Data

In this paper, we discuss a technique for discovering localized associations in segments of the data using clustering. Often the aggregate behavior of a data set may be very di erent from localized segments. In such cases, it is desirable to design algorithms which are e ective in discovering localized associations, because they expose a customer pattern which is more speci c than the aggregate behavior. This information may be very useful for target marketing. We present empirical results which show that the method is indeed able to nd a signi cantly larger number of associations than what can be discovered by analysis of the aggregate data.