The Shannon Entropy Correlation was recently applied in metabolomics and has been proposed to outperform the Cosine Correlation with respect to AUC and false discovery rate in small-molecule compound identification. The Shannon Entropy Correlation measures the entropy distance between I and J and then normalizes this entropy distance in such a way to bound the similarity score between 0 and 1 with the desired property of dissimilar spectra having similarity close to 0 and similar spectra having similarity close to 1. The Shannon Correlation is computed as