Text fusion based internet of things service recommendation for trigger⁃action programming pattern

被引：0
|
作者：
Sun D.-M. [1 ]
Hu L. [1 ]
Xing Y.-H. [1 ]
Wang F. [1 ]
机构：
[1] College of Computer Science and Technology, Jilin University, Changchun
来源：
Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition) | 2021年 / 51卷 / 06期
关键词：
Computer application; Heterogeneous information network; Internet of things; Text analysis; Trigger-action programming pattern;
D O I：
10.13229/j.cnki.jdxbgxb20210848
中图分类号：
学科分类号：
摘要：
This article proposes a service recommendation approach for a type of Internet of Things (IoT) automation-driven applications. The approach combines text analysis, heterogeneous information networks and deep learning to find related objects in the IoT by analyzing text, and then recommends the services. First, we construct a text fusion heterogeneous information network, which integrates text and text relationships. Then we design meta-paths and relationship weights. Finally, we train a neural network model for recommending the services. This paper conducts an experimental evaluation on a real data set. The results show that the proposed approach can be used for recommendation task and outperforms some classical methods. © 2021, Jilin University Press. All right reserved.
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页码：2182 / 2189
页数：7
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