Research on link prediction model based on hierarchical attention mechanism
In order to solve the problem that the existing graph attention mechanism tends to cause attention distribution to certain relations with high frequency when performing link prediction related tasks, a new link prediction model based on hierarchical attention mechanism was proposed.In the link predi...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2021-03-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021057/ |
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| _version_ | 1850123215639150592 |
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| author | Xiaojuan ZHAO Yan JIA Aiping LI Kai CHEN |
| author_facet | Xiaojuan ZHAO Yan JIA Aiping LI Kai CHEN |
| author_sort | Xiaojuan ZHAO |
| collection | DOAJ |
| description | In order to solve the problem that the existing graph attention mechanism tends to cause attention distribution to certain relations with high frequency when performing link prediction related tasks, a new link prediction model based on hierarchical attention mechanism was proposed.In the link prediction task, a hierarchical attention mechanism was designed to give different attention to the relationships of different relationship types connected to a given entity in the knowledge graph according to the relationship in the prediction task.While the characteristics of multi-hop neighbor entities were pay attention to, the relationship characteristics was pay more attention to find the relationship type that matches the target relationship.Through comparison experiments with the mainstream models on multiple benchmark data sets, the results show that the performance of the model is better than the mainstream models and has good robustness. |
| format | Article |
| id | doaj-art-cbc11048b6a042fdbd047e49a8abda66 |
| institution | OA Journals |
| issn | 1000-436X |
| language | zho |
| publishDate | 2021-03-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-cbc11048b6a042fdbd047e49a8abda662025-08-20T02:34:39ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2021-03-0142364459740616Research on link prediction model based on hierarchical attention mechanismXiaojuan ZHAOYan JIAAiping LIKai CHENIn order to solve the problem that the existing graph attention mechanism tends to cause attention distribution to certain relations with high frequency when performing link prediction related tasks, a new link prediction model based on hierarchical attention mechanism was proposed.In the link prediction task, a hierarchical attention mechanism was designed to give different attention to the relationships of different relationship types connected to a given entity in the knowledge graph according to the relationship in the prediction task.While the characteristics of multi-hop neighbor entities were pay attention to, the relationship characteristics was pay more attention to find the relationship type that matches the target relationship.Through comparison experiments with the mainstream models on multiple benchmark data sets, the results show that the performance of the model is better than the mainstream models and has good robustness.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021057/hierarchical attention mechanismlink predictionknowledge graph embedding |
| spellingShingle | Xiaojuan ZHAO Yan JIA Aiping LI Kai CHEN Research on link prediction model based on hierarchical attention mechanism Tongxin xuebao hierarchical attention mechanism link prediction knowledge graph embedding |
| title | Research on link prediction model based on hierarchical attention mechanism |
| title_full | Research on link prediction model based on hierarchical attention mechanism |
| title_fullStr | Research on link prediction model based on hierarchical attention mechanism |
| title_full_unstemmed | Research on link prediction model based on hierarchical attention mechanism |
| title_short | Research on link prediction model based on hierarchical attention mechanism |
| title_sort | research on link prediction model based on hierarchical attention mechanism |
| topic | hierarchical attention mechanism link prediction knowledge graph embedding |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021057/ |
| work_keys_str_mv | AT xiaojuanzhao researchonlinkpredictionmodelbasedonhierarchicalattentionmechanism AT yanjia researchonlinkpredictionmodelbasedonhierarchicalattentionmechanism AT aipingli researchonlinkpredictionmodelbasedonhierarchicalattentionmechanism AT kaichen researchonlinkpredictionmodelbasedonhierarchicalattentionmechanism |