We consider a new problem of detecting members of a rare class of data, the needles, which have been hidden in a set of records, the haystack. The only information regarding the characterization of the rare class is a single instance of a needle. It is assumed that members of the needle class are similar to each other according to an unknown needle characterization. The goal is to find the needle records hidden in the haystack. This paper describes an algorithm for that task and applies it to several example cases.
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