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Dual-chain Unequal-state CRF for Chinese New Word Detection and POS Tagging

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In Chinese language processing， new words are particularly problematic。 It is impossible to get a complete dictionary as new words can always be created。 We proposed a unified Dual-chain unequal-state CRF model to detect new words together with their part-of-speech in Chinese texts regardless of the word types such as compound words， abbreviation， person names， etc。 The Dual-chain Unequal-state CRF model has two state chains with unequal number of states。 The unequal state chains could model flexible hierarchical lexical information for both Chinese new word detection and POS tagging， and also integrate complex context features like the global information。 The experimental results show that the proposed method is capable of detecting even low frequency new words and their parts-of-speech synchronously with satisfactory results。

new word detectiondual-chain unequal-state CRFPOS tagging

Xiao SUN、Fuji REN、Degen HUANG

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Dept.of Information Science & Intelligent Systems,Tokushima University,Tokushima,Japan

Dept.of Computer Science & Engineering,Dalian University of Technology,Liaoning,China

北京

The 2008 IEEE International Conference on Natural Language Processing and Knowledge Engineering（IEEE NLP-KE 2008）(2008IEEE自然语言处理与知识工程国际会议)论文集

2008