Similarity measure is an important method to measure the similarity between two intuitionsitic fuzzy sets. Many formulas about similarity measure have been proposed, but some are unable to classify or involve complicated calculation in practical applications. To solve this problem, based on the cotangent similarity measurement method proposed by Tian and the information carried by the membership degree, nonmembership degree and hesitancy degree, we propose two sine similarity measure formulas which prove to be correct. Then we conduct comparative analysis among various similarity measures by several numerical examples to illustrate the effectiveness of the proposed sine similarity measures. Finally, the effectiveness of the method is illustrated by an example.