知识图谱及其应用的最新趋势

S. Kannadhasan, R. Nagarajan
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引用次数: 0

摘要

在智能网络领域,信息图的表示引起了很多研究的兴趣。基于语言的方法将每个关系视为从头到尾的单个翻译,如Trans E, Trans H和Trans R,简单,高效,达到了艺术状态的效率。信息图以节点(实体)之间带有标记边(关系)的图的形式传达知识。信息图的完成是预测实体之间缺失关系的基本活动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recent Trends in Knowledge Graphs and its Applications
: In the area of the Intelligent Network, the representations of an information graph have sparked a lot of research interest. Language-based approaches treat each relationship as a single translation from head to tail like Trans E, Trans H and Trans R are simple, efficient and achieving the art state efficiency. Information graphs convey knowledge as a graph with marked edges (relationships) between nodes (entities). The completion of the information graph is an essential activity aimed at predicting the missing relationship between entities.
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