Many online data sources are updated autonomously and independently.
In this paper, we make the case for estimating the change frequency
of the data, to improve web crawlers, web caches and to help data mining.
We first identify various scenarios, where different applications
have different requirements on the accuracy of the estimated frequency.
Then we develop several "frequency estimators"
for the identified scenarios.
In developing the estimators, we analytically show how precise/effective
the estimators are, and we show that the estimators that we propose
can improve precision significantly.