Abstract

Knowledge graph question answering (KGQA) uses structured knowledge in the knowledge graph (KG) to answer natural language questions. Currently, simple question answering has been well solved, but the performance of complex question answering needs to be improved. In this survey, we first present the background knowledge about complex question answering based on KG. Then the information retrieval-based (IR-based) method is introduced. We describe each procedure in the IR-based method in detail and investigate the related tools. Finally, the work is summarized and future research is envisioned based on the problems of current the IR-based method directions. With this survey, we aim to provide novices in the field of KGQA with an entry point to a suitable the IR-based method, where each step of the method can be understood.

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