Abstract: News summary report can effectively solve the problem of reading large number of news. News topic clustering is a good way to find potential hot spots and views. News trend, relations with topics and entities can be mined from news topics. Keywords and topics sentences can be extracted from the news topics. All these semantic information mined from news topics give a good show from mutil-angle. These information are good materials for the news summary report with help of the given wording rules. Then a news summary report with thorough analysis and rich charts is automatically created.

Key words: news summary, topic modeling, topic sentence extraction, writing rules

摘要： 利用新闻事件的话题、实体及其关联和发展趋势分析, 建立对新闻事件分析报告模型。该模型可以从多个角度描述新闻事件, 并依照新闻综述报告的写作特点, 制定出一种计算机自动分析报告生成的框架, 对新闻事件在话题和实体上的分析结果进行组合, 自动生成一篇观点分析透彻、图表信息生动准确的新闻事件分析报告。

关键词: 新闻综述, 话题模型, 主题句提取, 行文规则