Abstract

Transaction data can arrive at a ferocious rate in the or-der that transactions are completed. The data contain an enormous amount of information about customers, not just transactions, but extracting up-to-date customer informa-tion from an ever changing stream of data and mining it in real-time is a challenge. This paper describes a statistically principled approach to designing short, accurate summaries or signatures of high dimensional customer behavior that can be kept current with a stream of transactions. A signature database can then be used for data mining and to provide approximate answers to many kinds of queries about current customers quickly and accurately, as an empirical study of the calling patterns of 96,000 wireless customers who maxie about 18 million wireless calls over a three month period shows.

Citations