一种基于路径选择的多模态领域知识问答方法

PMKBQA:A MULTIMODAL DOMAIN KNOWLEDGE QUESTION ANSWERING METHOD BASED ON PATH SELECTION

  • 摘要: 基于知识图谱的问答领域中存在着自然语言与结构化知识的差异性挑战,因此,提出一种利用谓词选择路径的方法 PMKBQA。构建多模态领域知识图谱和问题集;从问题中识别的主题实体出发,计算其边与问题谓词的相似度,以逐跳的方式生成答案路径,直到找到问题答案,并依据答案路径获取问题答案的相关图像;在领域问题集上使用广满宽度评估实验,结果表明该方法可以给用户提供满意的图像,同时在 QALD 数据集上进行问答效果的对比实验,结果表明该方法比基线方法在 F1 指标上有所提升。

     

    Abstract: There are different challenges between natural language and structured knowledge in the field of question answering based on knowledge graphs. Therefore, this paper proposes a method of using predicates to select paths (PMKBQA). A multimodal domain knowledge graph and question set were constructed. Starting from the subject entity identified in the question, calculating the similarity between its edge and the question predicate, and generating the answer path hop by hop until the answer to the question was found. Relevant images of the answer of the question according to the answer path were acquired. The user satisfaction evaluation experiment was done on the domain question set, and the results show that this paper can provide users with satisfactory images. Meanwhile, a question answering effect evaluation experiment is done on the QALD data set, and the results show that our method is better than the baseline method in F1.

     

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