Papers with HITS algorithm
Ranking-Based Automatic Seed Selection and Noise Reduction for Weakly Supervised Relation Extraction (P18-2)
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| Challenge: | et al., 1998: bootstrapping for relation extraction uses minimally supervised methods . etudes show that proposed methods for automatic seed selection and noise reduction are better than baseline systems . |
| Approach: | They propose automatic seed selection and noise reduction for distantly supervised relation extraction tasks. |
| Outcome: | The proposed methods achieve better performance than baseline systems in both tasks. |
Graph-based Filtering of Out-of-Vocabulary Words for Encoder-Decoder Models (P18-3)
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| Challenge: | Encoder-decoder models employ words that are frequently used in the training corpus but may still include noisy words. |
| Approach: | They propose a method for selecting more suitable words for learning encoders by utilizing co-occurrence information. |
| Outcome: | The proposed method outperforms the baseline method in Japanese-to-English translation and grammatical error correction tasks with an F-measure of 1.48 points higher. |