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Adaptive Semi supervised Learning for Cross domain Sentiment Classification

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Figure

Table 1: Summary of datasets.
Figure 1: Performance comparison. Average results over 5 runs with random initializations are reportedfor each neural method
Figure 2: Accuracy vs. percentage of unlabeled target training examples.
Table 2: Comparison of the top trigrams (each column) from the target domain (beauty) captured by the5 most positive-sentiment-related CNN filters learned on E!BT

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