A metrics-based meta-learning model with meta-pretraining for industrial knowledge graph construction
文献类型：期刊论文
| 作者 | Liu, Yangshengyan2,3; Gu, Fu1,2,3; Wu, Yijie2; Gu, Xinjian2,3; Guo, Jianfeng4,5 |
| 刊名 | COMPUTERS IN INDUSTRY
 |
| 出版日期 | 2022 |
| 卷号 | 143 |
| 关键词 | Industrial knowledge graph Few-shot text classification Meta-learning Deep metric learning Attribute-based fusion |
| ISSN号 | 0166-3615 |
| DOI | 10.1016/j.compind.2022.103753 |
| 文献子类 | Article |
| 英文摘要 | Isolated data silos and domain-specific knowledge pose challenges for knowledge graph construction in the manufacturing industry, where heterogeneous storage leads to distributed databases with complex schemas. In this article, a resource-based industrial knowledge graph is developed using a few-shot classification algorithm to save on labor and other related costs in industrial knowledge graph construction, and an attribute-based fusion strategy for data fusion and alignment is designed. We also propose a novel metrics-based meta-learning model with meta-pretraining (MMM) to address the few-shot text classification problem. Experiment results show that MMM achieves 87.13% accuracy on the 5-shot text classification benchmark Amazon Review Sentiment Classification (ARSC), outperforming other baselines, such as Induction Networks (85.63%) and Distributional Signatures (81.16%). The MMM achieves a 34.6% accuracy improvement compared with Distributional Signatures (84.34% vs. 62.66%) on 1-shot problems of ARSC, hence highlighting the applicability of our model in low-resource conditions. Based on the proposed methods, we further develop an industrial knowledge graph platform with industrial applications, such as value chain analysis and collaboration, to improve knowledge reuse and service innovation. |
| WOS关键词 | CLASSIFICATION |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000930943800001 |
| 源URL | [http://ir.casisd.cn/handle/190111/12080]  |
| 专题 | 智库建设研究部 |
| 作者单位 | 1.Zhejiang Univ, Dept Ind & Syst Engn, Hangzhou 310027, Peoples R China 2.Zhejiang Univ, Key Lab Adv Mfg Technol Zhejiang Prov, Hangzhou 310027, Peoples R China 3.Zhejiang Univ, State Key Lab Fluid Power & Mechatron Syst, Hangzhou 310027, Peoples R China 4.Zhejiang Univ, Ctr Engn Management, Polytech Inst, Hangzhou 310015, Peoples R China 5.Univ Chinese Acad Sci, Sch Publ Policy & Management, Beijing 100049, Peoples R China 6.Chinese Acad Sci, Inst Sci & Dev, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Yangshengyan,Gu, Fu,Wu, Yijie,et al. A metrics-based meta-learning model with meta-pretraining for industrial knowledge graph construction[J]. COMPUTERS IN INDUSTRY,2022,143. |
| APA | Liu, Yangshengyan,Gu, Fu,Wu, Yijie,Gu, Xinjian,&Guo, Jianfeng.(2022).A metrics-based meta-learning model with meta-pretraining for industrial knowledge graph construction.COMPUTERS IN INDUSTRY,143. |
| MLA | Liu, Yangshengyan,et al."A metrics-based meta-learning model with meta-pretraining for industrial knowledge graph construction".COMPUTERS IN INDUSTRY 143(2022). |
入库方式： OAI收割
来源：科技战略咨询研究院
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。