A method to measure similarity between semantic graphs and its applications
Weijie Liu, Zhou Xue, Shujing Che, Xiang Yu, Zhiran Chen · 2023
Semantic search in information retrieval processes plays a crucial role in many application fields, such as product recommendation, personnel search, and those that require information matching. In most semantic search systems, semantic similarity technology is already indispensable. User queries can generate many query graphs. These query graphs can then be used to help users generate search results. Semantic similarity technology focuses on measuring the semantic similarity or semantic distance between two concepts. This paper mainly studies using semantic similarity technology to sort query graphs. To represent the similarity between semantic graphs, we calculate semantic distances. Unlike traditional semantic distance calculation methods, we calculate the distance between graphs. Experiments have confirmed the effectiveness and effectiveness of the method proposed in this paper.