摘要
将文本按事件方式进行表示,把事件作为基本语义单元来构建事件本体。根据事件间的关系构建事件网络有向图能较好地表达文本的语义信息及事件间的关系重要程度。利用PAGERANK算法测算事件网络图中各节点对应事件的重要度并进行排序,按事件发生的时间顺序,输出事件对应的原语句作为摘要。实验结果表明,基于事件网络的文本自动文摘方法抽取出的摘要效果较好。
Text was expressed by the means of event,and event ontology was built by using event as the basic semantic unit.According to the relationship between events,we built event network direct diagram which can express more semantic information of the text and describe the importance of relationship between events.The importance degree of event of the event network corresponding to each node was calculated and ranked by using the PAGERANK algorithm.According to the time sequence of events,event corresponding primitives were exported as abstract.The experimental results show that automatic summary based on the event network method has better performance.
出处
《计算机科学》
CSCD
北大核心
2015年第3期210-213,223,共5页
Computer Science
基金
国家自然科学基金项目(61273328
61305053)资助
