An Online Question Answering System based on Sub-graph Searching

TL;DR

This paper introduces a sub-graph searching mechanism for knowledge graph-based question answering systems, significantly improving speed and coverage in real-time online QA applications.

Contribution

It proposes a sub-graph index approach to enhance answer retrieval speed and coverage in large-scale knowledge graph question answering systems.

Findings

Improved answer retrieval speed in online QA systems.

Enhanced question coverage for entity-based questions.

High user experience due to fast response times.

Abstract

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.