Similarity metric is important in many applications. In some applications, it is desirable to normalize the similar- ity metric so as to yield a more meaningful insight of the situation, for example, in comparison of long genomic se- quences and comparative gene prediction. In extending the content of a previous work involving formal definition of the concept known as similarity, we give new formulas for normalizing similarity metrics which satisfy the formal defi- nition of the normalized similarity metric. We also describe how these formulas may be utilized in an appropriate ap- plication domain in which the use of normalized similarity metric is desirable.