LABELED AND PSEUDO-LABELED TEXTS

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Challenge:	Semi-Supervised Text Classification (SSTC) is a type of self-training that uses labeled and unlabeled data to perform certain applications.
Approach:	They propose a method to initialize a deep classifier by training over labeled texts . they then alternatively predict unlabeled texts as their pseudo-labels and train them over the mixture .
Outcome:	Empirical results show that the proposed method is more accurate when labeled texts are scarce.

Papers with labeled and pseudo-labeled texts