Abstract
Collocation describes how a word is used in relation to others in a language and extraction of collocations has a wide range of applications in both language learning and natural language processing. Verb-Object collocations is the most important part due to verb pivotal position in a sentence. In this paper, we present an efficient statistical algorithm for extracting verb-object collocations in Chinese in which three statistical features are combined. In our experiments the algorithm obtains precisions of 94.7% and 81.2% respectively for closed test and open test. The error analysis shows that the performance can be improved by applying shallow parsing technique as a preprocessor and adding more data for training.
| Keywords: | verb-object collocation; syntactic Parsing; probability; distribution |
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