Automatic Generation of Knowledge Base from Infrared Spectral Database for Substructure Recognition

This paper presents a new methodology of chemical substructure recognition by interpretation of an infrared spectrum. The approach in spectrum interpretation is based on the determination of functional groups, which may be present or absent in compounds whose structure is unimown. The process of searching for spectrumsubstructure correlation is realized by application of a statistical algorithm. In this method, correlations are generalized and condensed into a set of interpretation rules which are applied to the interpretation of an unknown compoundʹs spectrum in order to predict whether the respective substructures are present or absent in the unknown molecule.