具有层次实体类型和内容的知识图谱中的实体检索

Xinshi Lin, Wai Lam, K. Lai
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引用次数: 6

摘要

我们研究了从具有层次实体类型和实体描述的知识图中进行自组织实体检索的任务。我们的模型通过路径感知平滑方法将它们直接编码到基于马尔可夫随机场的框架中。我们在最近的基准数据集上进行了实验,并研究了维基百科类型和文章信息的结合。结果表明,我们的框架实现了现有的和最先进的模型的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Entity Retrieval in the Knowledge Graph with Hierarchical Entity Type and Content
We investigate the task of ad-hoc entity retrieval from a knowledge graph with hierarchical entity types and entity descriptions. Our model directly encodes them into a Markov random field based framework via a path aware smoothing method. We conduct experiments on recent benchmark datasets and investigate the incorporation of the Wikipedia type and article information. The results show that our framework achieves improvements over the existing and state-of-the-art models.
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