English morphological analysis with machine-learned rules

被引：0
|
作者：
Tang, Xuri [1 ]
机构：
[1] Wuhan Univ Sci & Engn, Dept Foreign Languages, Wuhan 430073, Peoples R China
来源：
PACLIC 20: Proceedings of the 20th Pacific Asia Conference on Language, Information and Computation | 2006年
关键词：
morphological analysis; statistical learning; intersectional ambiguity; combinatory ambiguity; wordform formation order;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper expounds an algorithm for morphological analysis of English language. The algorithm consists of two closely related components: morphological rule learning and morphological analyzing. The morphological rules are obtained through statistical learning from wordlist, with particular morphological features of English language taken into consideration. The procedure of morphological analysis considers two types of ambiguities: intersectional ambiguity and combinatory ambiguity. The procedure also considers the order of wordform formation in the language. Experiment shows that the algorithm performs distinctively compared to other algorithms.
引用
收藏
页码：35 / 41
页数：7
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