A novel reasoning mechanism for multi-label text classification

•A novel reasoning-based algorithm named ML-Reasoner for multi-label text classification is proposed.•Each instance of reasoning in this method takes the previously predicted likelihoods for all labels as additional input.•Not only is the method able to avoid the dependency of label orders completely, but it also achieves competitive performance when handling with multi-label datasets.•Applying the reasoning mechanism to three strong neural-based base models can achieve significant performance improvements on all two data sets.•The method achieves state-of-the-art results on two challenging multi-label datasets.