English Morphological Analysis with Machine-learned Rules
نویسنده
چکیده
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. Keyword: Morphological analysis; statistical learning; intersectional ambiguity; combinatory ambiguity; wordform formation order
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تاریخ انتشار 2006