Clause Splitting with Conditional Random Fields
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概要
- 論文の詳細を見る
In this paper, we present a Conditional Random Fields (CRFs) framework for the Clause Splitting problem. We adapt the CRFs model to this problem in order to use very large sets of arbitrary, overlapping and non-independent features. We also extend N-best list by using the Joint-CRFs (Shi and Wang 2007). In addition, we propose the use of rich linguistic information along with a new bottom-up dynamic algorithm for decoding to split a sentence into clauses. The experiments show that our results are competitive with the state-of-the art results.
- The Association for Natureal Language Processingの論文
著者
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Shimazu Akira
School Of Information Science Japan Advanced Institute Of Science And Technology
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Nguyen Minh
School Of Information Science Japan Advanced Institute Of Science And Technology
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Nguyen Vinh
School of Information Science, Japan Advanced Institute of Science and Technology
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Nguyen Minh
School of Information Science, Japan Advanced Institute of Science and Technology
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