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LREC
2010

Automatic Acquisition of Chinese Novel Noun Compounds

8 years 11 months ago
Automatic Acquisition of Chinese Novel Noun Compounds
Automatic acquisition of novel compounds is notoriously difficult because most novel compounds have relatively low frequency in a corpus. The current study proposes a new method to deal with the novel compound acquisition challenge. We model this task as a two-class classification problem in which a candidate compound is either classified as a compound or a non-compound. A machine learning method using SVM, incorporating two types of linguistically motivated features: semantic features and character features, is applied to identify rare but valid noun compounds. We explore two kinds of training data: one is virtual training data which is obtained by three statistical scores, i.e. co-occurrence frequency, mutual information and dependent ratio, from the frequent compounds; the other is real training data which is randomly selected from the infrequent compounds. We conduct comparative experiments, and the experimental results show that even with limited direct evidence in the corpus for...
Meng Wang, Chu-Ren Huang, Shiwen Yu, Weiwei Sun
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2010
Where LREC
Authors Meng Wang, Chu-Ren Huang, Shiwen Yu, Weiwei Sun
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