Estimating the rate at which events happen has been
studied under various guises and in different settings.
We are interested in the specific case of consumerinitiated
events or transactions (credit/debit card
transactions, mobile phone calls, online purchases,
etc.), and the modeling of such behavior, in order
to estimate the rate at which such transactions are
made. In this paper, we detail a model of such events
and a Bayesian approach, utilizing Sequential Monte
Carlo technology, to online estimation of the event
rate from event observations alone.
|Cite as: Honnappa, H. (2008). Customer Event Rate Estimation Using Particle Filters. In Proc. Seventh Australasian Data Mining Conference (AusDM 2008), Glenelg, South Australia. CRPIT, 87. Roddick, J. F., Li, J., Christen, P. and Kennedy, P. J., Eds. ACS. 61-72. |
(local if available)