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![既存手法(1) - 文字ベースのモデル
系列ラベリングとして定式化 [Xue, 2003]
– 各文字に対して、単語の境界かどうかのラベルを付ける
– CRFがstate-of-the-art [Lafferty et al., 2001]...](https://image.slidesharecdn.com/acl2014-140714043153-phpapp01/75/ACL-2014-PFI-Two-Knives-Cut-Better-Than-One-Chinese-Word-Segmentation-with-Dual-Decomposition-7-2048.jpg?cb=1667922607)
![既存手法(2) - 単語ベースのモデル
スコア関数を使って単語分割の候補(リスト)を探索
– 辞書を使った最大マッチング [Chen and Liu, 1992]
– 線形モデル(average perceptron) [Collins, ...](https://image.slidesharecdn.com/acl2014-140714043153-phpapp01/75/ACL-2014-PFI-Two-Knives-Cut-Better-Than-One-Chinese-Word-Segmentation-with-Dual-Decomposition-8-2048.jpg?cb=1667922607)
![既存手法(3) - 文字ベース/単語ベースの組み合わせ
のモデル
モデルが複雑な手法 [Sun et al., 2009]
– 学習に時間がかかる
特徴のbagging(?) [Wang et al., 2006], [Sun, 201...](https://image.slidesharecdn.com/acl2014-140714043153-phpapp01/75/ACL-2014-PFI-Two-Knives-Cut-Better-Than-One-Chinese-Word-Segmentation-with-Dual-Decomposition-9-2048.jpg?cb=1667922607)
![実験
モデルの組み合わせとハイパーパラメーター
– 文字ベースのモデル
Stanford CRF segmenter [Tseng et al., 2005]
L2正則化項のλは3
– 単語ベースのモデル
Perceptron ...](https://image.slidesharecdn.com/acl2014-140714043153-phpapp01/75/ACL-2014-PFI-Two-Knives-Cut-Better-Than-One-Chinese-Word-Segmentation-with-Dual-Decomposition-14-2048.jpg?cb=1667922607)
