Systems and methods for clustering-based text classification are described. In one aspect text is clustered as a function of labeled data to generate cluster(s). The text includes the labeled data and unlabeled data. Expanded labeled data is then generated as a function of the cluster(s). The expanded label data includes the labeled data and at least a portion of unlabeled data. Discriminative classifier(s) are then trained based on the expanded labeled data and remaining ones of the unlabeled data.
RELATED APPLICATIONS
This patent application claims priority to U.S. provisional patent application Ser. No. 60/562,911, titled "Clustering Based Text Classification", filed on Apr. 15, 2004, which is hereby incorporated by reference.
