An Online Question Answering System based on Sub-graph Searching
This work addresses the need for faster and more efficient entity-based question answering in online systems, though it appears incremental as it builds on existing knowledge graph methods.
The paper tackles the problem of slow answer retrieval from large knowledge graphs in online question answering by proposing a sub-graph searching mechanism with sub-graph indexing, resulting in improved question coverage and high speed for user experience.
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.