Abstract: Systems, method, and computer-readable mediums for automated text classification, and particularly a mechanism for performing binary classification using only a set of positive labeled data as training data and having a large set of unlabeled data, where the algorithm can function without any information regarding the negative class. The disclosed classification systems and methods may use a text classification process which automatically classifies text based on the current positive training data available, but identifies additional words which can be added to the positive training data such that future iterations of the text classification can better identify the positive class of text.

Abstract: Systems, method, and computer-readable mediums for automated text classification, and particularly a mechanism for performing binary classification using only a set of positive labeled data as training data and having a large set of unlabeled data, where the algorithm can function without any information regarding the negative class. The disclosed classification systems and methods may use a text classification process which automatically classifies text based on the current positive training data available, but identifies additional words which can be added to the positive training data such that future iterations of the text classification can better identify the positive class of text.