Knowledge graphs (KGs) have been widely used for question answering (QA) applications, especially the entity based QA. However, searching an-swers from an entire large-scale knowledge graph is very time-consuming and it is hard to meet the speed need of real online QA systems. In this pa-per, we design a sub-graph searching mechanism to solve this problem by creating sub-graph index, and each answer generation step is restricted in the sub-graph level. We use this mechanism into a real online QA chat system, and it can bring obvious improvement on question coverage by well answer-ing entity based questions, and it can be with a very high speed, which en-sures the user experience of online QA.
翻译:知识图表(KGs)被广泛用于问答应用程序,特别是基于实体的QA。然而,从整个大型知识图表中搜索一个答案非常耗时,很难满足真正的在线QA系统的速度需求。在这个Pa-per中,我们设计了一个子图搜索机制,通过创建子图索引来解决这一问题,在子图一级,每个答案生成步骤都受到限制。我们将这个机制用于一个真正的在线QA聊天系统,它可以通过回答实体的问题,使问题覆盖面明显改善,而且它可以非常快速地保证在线QA的用户经验。