Mining streams is a challenging problem, because the data can only be looked at once, and only small summaries of the data can be stored. We present a new frequency measure for items in streams that does not rely on a fixed window length or a time-decaying factor. Based on the properties of the measure, an algorithm to compute it is shown. Experimental evaluation supports the claim that the new measure can be computed from a summary with very small memory requirements, that can be maintained and updated efficiently. In this extended abstract, the main points of the presentation are discussed.