Raising the compatibility of heterogeneous annotations: a case study on protein mention recognition (自然言語処理・音声言語情報処理)
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概要
- 論文の詳細を見る
The use of human-annotated corpora is popular in developing language processing systems. For bio-text mining, for example, there are several well-known corpora with protein mention annotations. Because of the different conventions adopted by these corpora, one problem that is well recognized, but yet less addressed is brought about ; the problem is the heterogeneity of the corpora. The problem weakens the protein annotation consistency. In this work, we seek a way of removing or relaxing the heterogeneity of annotations by identifying and removing the specific difference between the annotations. Our results show that our effort to remove several disagreements between the corpora annotation is successful in reducing the performance degradation caused by heterogeneity and incompatibility.
- 一般社団法人情報処理学会の論文
- 2008-05-15
著者
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YOSHIDA Kazuhiro
Department of Surgical Oncology, Gifu University
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Wang Yue
Department Of Computer Science University Of Tokyo
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Kim Jin-dong
Department Of Computer Science University Of Tokyo
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Tsujii Jun'ichi
Department Of Computer Science University Of Tokyo:school Of Informatics University Of Manchester:na
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Seatre Rune
Department of Computer Science, University of Tokyo
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Yoshida Kazuhiro
Department Of Computer Science University Of Tokyo
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Yoshida Kazuhiro
Department Of Biotechnology Graduate School Of Engineering Nagoya University
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Seatre Rune
Department Of Computer Science University Of Tokyo
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Wang Yue
Department Of Applied Chemistry Beijing Institute Of Petrochemical Technology
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