Deep Attentional Factorization Machines Learning Approach for Driving Safety Risk Prediction
文献类型：期刊论文
| 作者 | Zhang,Jun1,2,3 ; Wu,Zhongcheng1,2; Li,Fang1; Li,Wenjing1,2; Ren,Tingting1; Li,Wei1; Chen,Jie1,2
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| 刊名 | Journal of Physics: Conference Series
 |
| 出版日期 | 2021 |
| 卷号 | 1732 |
| ISSN号 | 1742-6588 |
| DOI | 10.1088/1742-6596/1732/1/012007 |
| 英文摘要 | Abstract The data of Internet of Vehicles (IoV) can be used to evaluate the driving safety risk of auto insurance policyholder and provide technical means for Usage Based Insurance (UBI). There are many types of IoV data, such as continuous or ordinal, categorical, binary etc., which contain highly sparse and dimensional features after One-Hot processing, thus they learning the interaction between critical features and training predictive model difficult. Furthermore, some of the available data have been desensitized, so it is impossible to perform feature engineering based on experience. We propose an end-to-end deep learning framework named Deep Attentional Factorization Machine (DeepAFM), which combines the power of attentional factorization machine with deep learning for feature learning in a new neural network architecture. Compared with existing deep learning models, our approach can learn the weighted interactions between various features effectively by introducing the structure of feature fields without feature engineering. Experimental results showed that our model yields excellent results in real-world data. |
| 语种 | 英语 |
| WOS记录号 | IOP:JPCS_1732_1_012007 |
| 出版者 | IOP Publishing |
| 源URL | [http://ir.hfcas.ac.cn:8080/handle/334002/127367]  |
| 专题 | 中国科学院合肥物质科学研究院 |
| 作者单位 | 1.High Magnetic Field Laboratory, and Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China 2.University of Science and Technology of China, Hefei 230026, China 3.Institute of Intelligent Machines, and Hefei Institute of Physical Science, Chinese Academy of Sciences, Hefei 230031, China |
| 推荐引用方式 GB/T 7714 | Zhang,Jun,Wu,Zhongcheng,Li,Fang,et al. Deep Attentional Factorization Machines Learning Approach for Driving Safety Risk Prediction[J]. Journal of Physics: Conference Series,2021,1732. |
| APA | Zhang,Jun.,Wu,Zhongcheng.,Li,Fang.,Li,Wenjing.,Ren,Tingting.,...&Chen,Jie.(2021).Deep Attentional Factorization Machines Learning Approach for Driving Safety Risk Prediction.Journal of Physics: Conference Series,1732. |
| MLA | Zhang,Jun,et al."Deep Attentional Factorization Machines Learning Approach for Driving Safety Risk Prediction".Journal of Physics: Conference Series 1732(2021). |
入库方式： OAI收割
来源：合肥物质科学研究院
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