Statistically-Enhanced New Word Identification In A Rule-Based Chinese System
نویسندگان
چکیده
This paper presents a mechanism of new word identification in Chinese text where probabilities are used to filter candidate character strings and to assign POS to the selected strings in a ruled-based system. This mechanism avoids the sparse data problem of pure statistical approaches and the over-generation problem of rule-based approaches. It improves parser coverage and provides a tool for the lexical acquisition of new words.
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تاریخ انتشار 2000