Seeing that the number of documents with at least one positive class is much less common compared to the number of documents without any positive class (see Table 1), simply taking a randomly sampled document from the unlabeled documents will likely give a document with no class, which is less useful compared to document with at least one positive class.
labeling: With the updated set of keywords for each class, we relabeled the documents to obtain a new set of labeled documents and again executed the clustering step to get more keywords.