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An Approach for Chinese-Japanese Named Entity Equivalents Extraction Using Inductive Learning and Hanzi-Kanji Mapping Table
Title: | An Approach for Chinese-Japanese Named Entity Equivalents Extraction Using Inductive Learning and Hanzi-Kanji Mapping Table |
Authors: | Xu, JinAn Browse this author | Chen, Yufeng Browse this author | Ru, Kuang Browse this author | Zhang, Yujie Browse this author | Araki, Kenji Browse this author →KAKEN DB |
Keywords: | named entity translation equivalents acquisition | Chinese Hanzi and Japanese Kanji mapping table | inductive learning | monolingual corpora |
Issue Date: | Aug-2017 |
Publisher: | 電子情報通信学会 |
Journal Title: | IEICE transactions on information and systems |
Volume: | E100D |
Issue: | 8 |
Start Page: | 1882 |
End Page: | 1892 |
Publisher DOI: | 10.1587/transinf.2016EDP7425 |
Abstract: | Named Entity Translation Equivalents extraction plays a critical role in machine translation (MT) and cross language information retrieval (CLIR). Traditional methods are often based on large-scale parallel or comparable corpora. However, the applicability of these studies is constrained, mainly because of the scarcity of parallel corpora of the required scale, especially for language pairs of Chinese and Japanese. In this paper, we propose a method considering the characteristics of Chinese and Japanese to automatically extract the Chinese-Japanese Named Entity (NE) translation equivalents based on inductive learning (IL) from monolingual corpora. The method adopts the Chinese Hanzi and Japanese Kanji Mapping Table (HKMT) to calculate the similarity of the NE instances between Japanese and Chinese. Then, we use IL to obtain partial translation rules for NEs by extracting the different parts from high similarity NE instances in Chinese and Japanese. In the end, the feedback processing updates the Chinese and Japanese NE entity similarity and rule sets. Experimental results show that our simple, efficient method, which overcomes the insufficiency of the traditional methods, which are severely dependent on bilingual resource. Compared with other methods, our method combines the language features of Chinese and Japanese with IL for automatically extracting NE pairs. Our use of a weak correlation bilingual text sets and minimal additional knowledge to extract NE pairs effectively reduces the cost of building the corpus and the need for additional knowledge. Our method may help to build a large-scale Chinese-Japanese NE translation dictionary using mono-lingual corpora. |
Rights: | Copyright ©2017 The Institute of Electronics, Information and Communication Engineers |
Relation: | https://search.ieice.org/ |
Type: | article |
URI: | http://hdl.handle.net/2115/67136 |
Appears in Collections: | 情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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Submitter: 荒木 健治
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