document: Mining a stream of transactions for customer patterns Transaction data can arrive at a ferocious rate in the order that transactions are completed . The data contain an enormous amount of information about customers , not just transactions , but extracting up-to-date customer information 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 made about 18 million wireless calls over a three month period shows .
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