Attention-based Multi-hop Reasoning for Knowledge Graph
Wang Zikang1,2; Li Linjing1; Zeng Daniel1,2; Chen Yue3
2018-11
会议名称IEEE International Conference on Intelligence and Security Informatics
会议日期2018.11.08-10
会议地点美国,迈阿密
摘要

Knowledge graph plays an important role in de- tection, prediction, early warning, and other security related applications. A fundamental task in applying knowledge graph is the so-called multi-hop reasoning, which focuses on inferring new relations between entities. In this paper, we introduce attention mechanism to the classic compositional method. After finding reasoning paths between entities, we aggregate these paths’ embeddings into one according to their attentions, and infer the relation of entities based on the combined embedding. Two experiments on NELL-995 dataset, fact prediction and link prediction, validated that our method outperforms all baselines.

文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/44374
专题复杂系统管理与控制国家重点实验室_互联网大数据与信息安全
作者单位1.The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences
2.CNCERT/CC
3.chool of Computer and Control Engineering, University of Chinese Academy of Sciences
第一作者单位中国科学院自动化研究所
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Wang Zikang,Li Linjing,Zeng Daniel,et al. Attention-based Multi-hop Reasoning for Knowledge Graph[C],2018.
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