Summarizing the Differences in Chinese-Vietnamese Bilingual News
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초록
Summarizing the differences in Chinese-Vietnamese bilingual news plays an important supporting role in thecomparative analysis of news views between China and Vietnam. Aiming at cross-language problems in theanalysis of the differences between Chinese and Vietnamese bilingual news, we propose a new method ofsummarizing the differences based on an undirected graph model. The method extracts elements to representthe sentences, and builds a bridge between different languages based on Wikipedia’s multilingual conceptdescription page. Firstly, we calculate the similarity between Chinese and Vietnamese news sentences, andfilter the bilingual sentences accordingly. Then we use the filtered sentences as nodes and the similarity gradeas the weight of the edge to construct an undirected graph model. Finally, combining the random walkalgorithm, the weight of the node is calculated according to the weight of the edge, and sentences with highestweight can be extracted as the difference summary. The experiment results show that our proposed approachachieved the highest score of 0.1837 on the annotated test set, which outperforms the state-of-the-artsummarization models.
Abstract
Summarizing the differences in Chinese-Vietnamese bilingual news plays an important supporting role in thecomparative analysis of news views between China and Vietnam. Aiming at cross-language problems in theanalysis of the differences between Chinese and Vietnamese bilingual news, we propose a new method ofsummarizing the differences based on an undirected graph model. The method extracts elements to representthe sentences, and builds a bridge between different languages based on Wikipedia’s multilingual conceptdescription page. Firstly, we calculate the similarity between Chinese and Vietnamese news sentences, andfilter the bilingual sentences accordingly. Then we use the filtered sentences as nodes and the similarity gradeas the weight of the edge to construct an undirected graph model. Finally, combining the random walkalgorithm, the weight of the node is calculated according to the weight of the edge, and sentences with highestweight can be extracted as the difference summary. The experiment results show that our proposed approachachieved the highest score of 0.1837 on the annotated test set, which outperforms the state-of-the-artsummarization models.
참고문헌 (26)
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