问答系统中的复杂问句通常涉及很多事件信息，正确处理其中的事件内容对提高系统准确率有重要的影响．为此，文中提出了一种融合事件信息的复杂问句分析方法．该方法将事件视为由多个要素构成的复杂数据对象，从而定义了事件的语义表征模型，给出了相似度计算方法．文中首先利用相关的事件抽取方法获取复杂问句中的事件信息，生成事件的语义模型实例．然后利用事件语义模型实例构成的矢量表征复杂问题的完整语义信息，从而根据表征矢量计算复杂问句的相似度．实验表明，事件语义信息对问句分析是有益的，融合事件信息的复杂问句分析方法有助于提高问答系统的整体性能，准确率高达78.6%．

The complex questions in the question answering ( QA) system usually involve much more event information. Proper processing of the event content is important for the accuracy improvement of QA system. In this paper,an analysis method of complex questions integrating event information is proposed,in which an event is considered as a complex data object containing multiple arguments,the semantic model of the event is defined,and the
similarity calculation method of the events is obtained. In the investigation,by using event extraction methods,the event information of a complex question is obtained to form event semantic model instances,and the whole semantic information of a complex question is then represented by a vector consisting of several semantic model instances. Consequently,the similarity of questions is calculated according to the vectors of semantic model instances of the event. Experimental results indicate that the semantic information of an event is helpful to the question analysis,and that the proposed analysis method of complex questions integrating event information improves the overall performance of QA system,with the accuracy being up to 78. 6%.