Abstract: Sequence labeling problem is a basic problem in natural language processing field. The task of sequence labeling is to label an input sequence with a label sequence of the same length. Under the fundamental framework of sequence labeling methods, a new online sequence labeling linear algorithm---confidence-weighted online sequence labeling algorithm---was presented for the characteristic of sequence labeling task with sparse features, based on confidence-weighted classification. This algorithm introduced a probabilistic measure of confidence for each parameter of features, and showed better performance than other relative algorithms. Experiments on Chinese segmentation, Chinese named entity recognition and English chunking validated the effectiveness of the proposed algorithm.