知识图谱技术在专利语义检索领域的应用研究

Research on Application of Knowledge Graph Technology in the Field of Patent Semantic Retrieval

[目的/意义]知识图谱作为近年来大数据、人工智能技术飞速发展背景下出现的知识探索、推理发现的新兴技术,对专利检索新业务形态开展,提升业务效率减轻人工负担有着广阔的应用前景。[方法/过程]通过对知识图谱构建流程、技术架构与专利文献业务特点分析结合,对知识图谱语义模型在低质量专利检索和可视化等场景应用进行了探讨。[结果/结论]知识图谱在专利检索场景中适用性较强,相关技术环境/工具成熟,同时其垂直领域多知识体系特点,其语义模型构建还需要高质量文献和专家进行协助和迭代。

[Purpose/significance]As an emerging technology of knowledge exploration and inference discovery emerging in the context of rapid development of big data and artificial intelligence technology in recent years,knowledge graph has broad application prospects for the development of new business forms of patent retrieval and the improvement of business efficiency to reduce the manual burden.[Method/process]By combining the analysis of knowledge graph construction process,technical architecture and patent literature business characteristics,the application of knowledge graph semantic model in scenarios such as low quality patent retrieval and visualization is explored.[Result/conclusion]Knowledge graph is highly applicable in patent retrieval scenarios,and the related technical environment/tools are mature,while its vertical domain multi-knowledge system characteristics,its semantic model construction still needs assistance and iteration from high-quality literature and experts.