Using Collaborative Training Method to Build Vietnamese Dependency Treebank
نویسندگان
چکیده
For the difficulty of marking Vietnamese dependency tree, this paper proposed the method which combined MST algorithm and improved Nivre algorithm to build Vietnamese dependency treebank. The method took full advantage of the characteristics of collaborative training. Firstly, we built a bit samples. Secondly, we used the samples to build two weak learners with two fully redundant views. Then, we marked a large number of unmarked samples mutually. Next, we selected the samples of high trust to relearn and built a dependency parsing system. Finally, we used 5000 Vietnamese sentences marked manually to do tenfold cross-test and obtained the accuracy of 76.33%. Experimental results showed that the proposed method in this paper could take full advantage of unmarked corpus to effectively improve the quality of dependency treebank.
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تاریخ انتشار 2016