Prompt-WNQA: A prompt-based complex question answering for wireless network over knowledge graph

Abstract

With the rapid development of wireless networks, the scale of network devices is constantly expanding. Experts spend vast amounts of time consulting and dealing with various network problems of the same nature during the course of daily network operation and maintenance service, and there is no time to collect statistics and sort their information, which affects the overall operation and maintenance efficiency. This paper investigates complex Knowledge Graph Question Answering (KGQA) in the wireless network domain in order to improve operation and maintenance efficiency. Accordingly, we propose Wireless Network QA over the KG using Prompt learning (Prompt-WNQA), a novel method that deals with both constraint-based and multi-hop complex questions making use of prompt learning. Our method is also helpful in performing complex KGQA over incomplete KGs, which can complete missing relations between unconnected entities. Compared to state-of-the-art approaches, our Prompt-WNQA achieves significant improvement over extensive experiments on both the wireless network QA dataset and two public complex QA datasets.