bitspec: Generate a Bit Spectrum from a List of Fingerprints
In fingerprint: Functions to Operate on Binary Fingerprint Data

Description Usage Arguments Value Author(s) References See Also

The idea of comparing datasets using fingerprints was described in Guha \& Schurer (2008). The idea is that one can summarize the dataset by counting the frequency of occurrence of each bit position. The frequency is normalized by the number of fingerprints considered. Thus a collection of N fingerprints can be converted to a single vector of numbers highlighting the most frequent bits with respect to a given dataset. A plot of this vector looks like a traditional spectrum and hence the name.

The bit spectra for two datasets (assuming that the same types of fingerprints have been used) allows one to compare the similarity of the datasets, without having to do a full pairwise similarity calculation. The difference between the structural features of the datasets can be quantified by evaluating the distance between the two bit spectra.