Guiding Dialogue Agents to Complex Semantic Targets by Dynamically Completing Knowledge Graph
Yue Tan, Bo Wang, Anqi Liu, Dongming Zhao, Kun Huang, Ruifang He, Yuexian Hou · 2023
In target-oriented dialogue, the representation and achievement of targets are two interrelated essential issues.In current approaches, the target is typically assumed to be a single object represented as a word, which makes it relatively easy to achieve through dialogue with the help of a knowledge graph (KG).However, when the target has complex semantics, the existing KG is often incomplete in tracking semantic relations.This paper studies target-oriented dialog where the target is a topic sentence.We combine the methods of knowledge retrieval and relationship prediction to construct a contextrelated dynamic KG, in which we can track the implicit semantic paths in the speaker's mind that may not exist in the existing KGs.In addition, we also designed a novel metric to evaluate the tracked path automatically.The experimental results show that our method can control the agent more logically and smoothly toward the complex target.