WANG Runfeng,LI Tongyan,GU Liping,et al.Behavior Modifier Embedding for Temporal Knowledge Graph Embedding[J].Journal of Chengdu University of Information Technology,2024,39(05):534-539.[doi:10.16836/j.cnki.jcuit.2024.05.003]
基于行为修饰嵌入的时序知识图谱嵌入研究
- Title:
- Behavior Modifier Embedding for Temporal Knowledge Graph Embedding
- 文章编号:
- 2096-1618(2024)05-0534-06
- 分类号:
- TP391.1
- 文献标志码:
- A
- 摘要:
- 随着时序知识图谱的不断发展与应用,时序知识图谱的嵌入作为时序知识图谱应用的桥梁,在时序知识图谱的研究中有着较高的地位。时序知识图谱嵌入模型也越来越受重视。根据词语间的修饰关系与修饰方式提出一种基于行为修饰实体的嵌入模型,并利用这一模型将时间嵌入到实体使四元组转变为三元组。之后将其与DistMult模型结合形成新的时序知识图谱嵌入模型,即BME-DistMult。在ICEWS14与GDELT数据集上进行实验,与现有的静态知识图谱嵌入模型和其他时序知识图谱嵌入模型进行对比,该模型有较好的效果。
- Abstract:
- With the continuous development and application of temporal knowledge graph, the research direction of embedding of temporal knowledge graph is a bridge for the application of temporal knowledge graph to various applications and has a high position in the research of temporal knowledge graph. The embedding model of the temporal knowledge graph has been paid more and more attention.This paper proposes an embedding model based on behavior modifiers based on modifying entities according to the modification relationship and modification mode between words and uses this model to embed time into entities to transform quadruples into triples. It is then combined with the DistMult model to form a new temporal knowledge graph embedding model,which is called BME-DistMult. Experiments are carried out on ICEWS14 and GDELT datasets,and compared with the existing static knowledge graph embedding model and other temporal knowledge graph embedding models,our model has good results.
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备注/Memo
收稿日期:2023-06-26
基金项目:四川省科技厅重点研发资助项目(2023YFS0422)