Abstract
Abstract There has been frequent interest in the chemical literature in describing methods for the rapid search of large data collections. Since these collections may contain 10 4 –10 5 entries, any similarity search is difficult. However if one number is assigned to each entry and that number retains all similarity information, then a simple binary search can produce the data collection entries that are most similar to an unknown. This approach is investigated for a file of gas chromatographic liquid phases and for a large set of mass spectra. Obvious limitations occur when the data are multi-dimensional. However indications of multi-dimensional similarity are retained even in the difficult mass spectral example.
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