Error-driven pruning of Treebank grammars for base noun phrase identification
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Text chunking by combining hand-crafted rules and memory-based learning
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
A unified statistical model for the identification of English baseNP
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Chunking with maximum entropy models
ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
Use of support vector learning for chunk identification
ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
The editing generator and its cryptanalysis
International Journal of Wireless and Mobile Computing
Important scene analysis model using result importance and situation importance
International Journal of Wireless and Mobile Computing
Design and implementation of transactional agent
International Journal of Wireless and Mobile Computing
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Aiming at the characteristics of Naxi language, a method is proposed for Naxi sentence similarity calculation. First, according to the characteristics of Naxi language that verbs set back, and nouns and verbs appear in chunks. Naxi NP and VP chunks are defined and chunk rule is extracted. According to the rules of the Naxi sentence chunking, extracts NP and VP chunks as so on. Then, by using the Naxi-Chinese dictionary, Naxi word is mapped to the Chinese word. By using the Chinese word similarity, Naxi words semantic similarity is calculated. Similarity of chunks is calculated by the combination of Chinese word similarity. Chunks similarity is defined as the replacement cost of chunk that edits operation, and Naxi sentence similarity is computed according to replacement cost. Finally, experiment is done to calculate Naxi sentence similarity. Experimental result shows that proposed method is better than other methods, and chunk exchange method can effectively improve the accuracy of the Naxi sentence similarity.