Difference between revisions of "C. Mota and R. Grishman. ACL-IJCNLP 2009"
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== Summary == | == Summary == | ||
| + | |||
[[UsesDataset::CETEMPublico]] | [[UsesDataset::CETEMPublico]] | ||
| − | [[Category::paper]] | + | In this [[Category::paper]], the authors tried to discover the roles of unlabeled data from different periods |
| + | in [[UsesMethod::semi-supervised learning]] on [[AddressesProblem::Name Entity Tagging]] task. | ||
| + | |||
| − | [[ | + | In the experiments, they use [[UsesDataset::CETEMPublico]] dataset. |
| + | They draw test set from the most recent epoch and varying the seeds set or the unlabeled data. | ||
| + | They found out: | ||
| + | # In training, adding more recent unlabeled data outperforms the strategy of adding contemporary labeled data. | ||
| + | # Adding more older unlabeled data did not improve the performance compared with adding a smaller set of contemporary unlabeled data. | ||
[[UsesMethod::Co-training]] | [[UsesMethod::Co-training]] | ||
Revision as of 14:59, 31 October 2010
Citation
C. Mota & R. Grishman. Updating a Name Tagger Using Contemporary Unlabeled Data. In Proceedings of the ACL-IJCNLP 2009 Conference Short Papers, 2009.
Online version
updating name tagger using unlabeled data
Summary
In this paper, the authors tried to discover the roles of unlabeled data from different periods in semi-supervised learning on Name Entity Tagging task.
In the experiments, they use CETEMPublico dataset.
They draw test set from the most recent epoch and varying the seeds set or the unlabeled data.
They found out:
- In training, adding more recent unlabeled data outperforms the strategy of adding contemporary labeled data.
- Adding more older unlabeled data did not improve the performance compared with adding a smaller set of contemporary unlabeled data.
