蒙文新闻事件检测新方法研究

Shijie Wang, F. Bao, Guanglai Gao
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引用次数: 2

摘要

新事件检测(NED)旨在从一个或多个新闻故事流中检测第一条新闻。本文以新闻领域为研究对象,对蒙古语新事件检测的相关方法进行了研究。本文提出了一种将新闻内容的相似度与新闻元素的相似度相结合来检测新事件的方法。对于新闻内容的表示,根据新闻的特点和不同新闻类别的不同词汇表达,对传统的TF-IDF方法进行改进。此外,提取新闻的主要元素,包括时间、地点、主语、宾语、标注,并计算两个新闻文档之间新闻元素的相似度。最后,结合新闻内容与新闻元素之间的相似度,计算出最终的相似度,用于新事件检测。实验结果表明,改进后的方法效果明显,与传统的新型事件检测系统相比,性能有明显提高。
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Research on New Event Detection Methods for Mongolian News
New event detection (NED) aims at detecting the first news from one or multiple streams of news stories. This paper is aimed at the field of journalism and studies the related methods of Mongolian new event detection. The paper proposes a method that combines the similarity of news content with the similarity of news elements to detect the new event. For the news content representation, according to the characteristics of the news and the different vocabulary expressions in different news categories, improve the traditional TF-IDF method. In addition, extract the main elements of the news, including time, place, subject, object, denoter, and calculate the similarity of news elements between the two news documents. Finally, the similarity between the news content and the news elements is combined to calculate the final similarity for new event detection. The experimental results show that the improved method is obvious, and the performance is significantly improved compared with the traditional new event detection system.
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