计算机科学 ›› 2022, Vol. 49 ›› Issue (11): 185-196.doi: 10.11896/jsjkx.211100063
邓亮1,2,3, 曹存根4
DENG Liang1,2,3, CAO Cun-gen4
摘要: 专利知识图谱对专利精准检索、专利深度分析和专利知识培训等应用起到了重要作用。文中提出了一种实用的基于种子知识图谱、文本挖掘以及关系补全的专利知识图谱构建方法。在该方法中,为确保质量,首先人工建立一个种子专利知识图谱,然后采用专利文本模式的概念和关系抽取方法扩展种子专利知识图谱,最后对扩展的专利知识图谱进行定量评估。文中针对中医药领域专利进行了种子知识的人工提取和词法句法模式的人工总结,并使用机器学习的方法在学习到新的词法句法模式后对种子专利知识图谱进行扩展和图谱补全。实验结果表明,中医药领域专利种子知识图谱中的节点数和关系数分别为19 453个和194 775条,经过扩展后,它们分别达到了558 461个和7 275 958条,即分别增加了27.7倍和36.3倍。
中图分类号:
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