In this paper, we present an efficient statistical algorithm for extracting verb-object collocations in Chinese in which three statistical features are combined.

Verb-Object collocations play an important role in parsing because of its long spread and strong combination competition.

This thesis takes the verb-object structure "zou/pao+N" for example to do research on the phenomenon of "Verb-Object extraordinary collocation", based on the "Theory of Clausal Government" which is the nucleus of the "Theory of Clausal Pivot".

A Study on Explicit Vocabulary Instructions in Verb Collocation;

Given by experience in the past,verbverb collocations are now automatically acquired by computing association degree of verb and verb followed with statistics method.

An Error Analysis of Verb-noun Collocations by Chinese EFL Learners;

According to the feature of verb-noun collocation structure,the method of mutual information is improved for identifying verb-noun collocation.

Using multivariate analyses, the study examined the roles of collocation knowledge, an important factor of vocabulary depth, specifically the role of Verb-Noun collocation and breadth of vocabulary knowledge in assessing the performance of a group of young adult ESL learners with a minimum vocabulary size of 3,000 word families in carrying out general academic read.