中文摘要：

针对汉越双语新闻话题文本集合中新闻话题要素提取的问题进行了研究，在超图模型的基础上，运用了PageRank随机游走排序方法。首先根据触发词激励的方法提取新闻中的事件要素，然后在此基础上构建话题超图模型，将汉越事件要素作为节点，将文本集合中的句子作为超边，根据概率评估函数计算节点和超边的初始权重，最后采用PageRank随机游走方法，对汉越事件要素进行评分，最终得到汉越话题要素。实验结果表明，该方法相比只考虑单文本事件要素提取方法的效果有显著提高。说明了基于超图的PageRank方法提取新闻话题要素的准确性。

英文摘要：

This paper studied the problems of news topic elements in the Chinese and Vietnamese bilingual news topic text collections. Based on hypergraph model extracted, it used the PageRank random walk ordering method. First according to the trigger word incentive method,it extracted the news event elements, and then on the basis of this,it constructed topic hyperg- raph model. It took the Chinese and Vietnamese elements as nodes and the sentences of text collection as a hyper-edge, it cal- culated the initial weights of nodes and hyperedges according to probability evaluation function. Finally, it used the PageRank random walk method to score the elements of the Chinese-Vietnamese event, and finally obtained the elements of the Chinese- Vietnamese topic. Results show that the proposed method can significantly improve the extraction performance compared to the method only considered single text event feature extraction. It shows the accuracy of extraction of news topicby PageRank me- thod based on hypergraph elements.