An optimal matching increasing weight algorithm for the unequal length sequence similarity measurement based on the sliding window is proposed to solve the unequal length sequence data association, which uses shorter sequences slide longer ones to get slidable similarity, forming the optimal weight with this similarity at the same time, then weighting the slidable similarity to get the unequal length sequence similarity. According to the degree of the sequence similarity, the judgment of the association of unequal length sequence data is obtained, which solves the local similarity problem of the truncated measurement algorithm. Simulation experiments show that the proposed algorithm can associate unequal length data effectively and also discuss the influence of the variation of sequence and measurement error on the sequence similarity and the association effect.