Semi-joint labeling for Chinese named entity recognition

Chia Wei Wu, Richard Tzong Han Tsai, Wen Lian Hsu

研究成果: 書貢獻/報告類型會議論文篇章同行評審

3 引文 斯高帕斯(Scopus)

摘要

Named entity recognition (NER) is an essential component of text mining applications. In Chinese sentences, words do not have delimiters; thus, incorporating word segmentation information into an NER model can improve its performance. Based on the framework of dynamic conditional random fields, we propose a novel labeling format, called semi-joint labeling which partially integrates word segmentation information and named entity tags for NER. The model enhances the interaction of segmentation tags and NER achieved by traditional approaches. Moreover, it allows us to consider interactions between multiple chains in a linear-chain model. We use data from the SIGHAN 2006 NER bakeoff to evaluate the proposed model. The experimental results demonstrate that our approach outperforms state-of-the-art systems.

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主出版物標題Information Retrieval Technology - 4th Asia Information Retrieval Symposium, AIRS 2008, Revised Selected Papers
頁面107-116
頁數10
DOIs
出版狀態已出版 - 2008
事件4th Asia Information Retrieval Symposium, AIRS 2008 - Harbin, China
持續時間: 15 1月 200818 1月 2008

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
4993 LNCS
ISSN(列印)0302-9743
ISSN(電子)1611-3349

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???event.eventtypes.event.conference???4th Asia Information Retrieval Symposium, AIRS 2008
國家/地區China
城市Harbin
期間15/01/0818/01/08

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