Geodesic
VDRF: Sensing the Defect Information to Risk Level of Vehicle Recall based on Bert Communication Model
Computer Science and Information Systems, Tome 17 (2020) no. 3.

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The recall of defective automobile products is one of the important measures to promote the quality of product quality and protect consumers' pyhsical safety and property security. In order to assess the risk level of defect cases, automobile recall management experts need to analyze and discuss the defect information by personal. A risk level prediction method based on language pre-training Bert model is proposed in this paper, which can transform the defect information into rick level of the vehicle and then predict vehicle recall automatically, in which a seq2seq model is proposed to multi-label the vehicle complaint data. The outputs of the seq2seq model combined with other static and dynamic information are used as the input of the Bert communication model. Substantial comparative experiments of different feature combinations on different methods show that the proposed VDRF method achieves F1 value with 79% in vehicle recall risk prediction, which outperforms the traditional method.
Keywords: Bert communication model, defect information transforming, multilabel classification, risk level prediction 
@article{CSIS_2020_17_3_a8,
     author = {Xindong You and Jiangwei Ma and Yuwen Zhang and Xueqiang Lv and Junmei Han},
     title = {VDRF: {Sensing} the {Defect} {Information} to {Risk} {Level} of {Vehicle} {Recall} based on {Bert} {Communication} {Model}},
     journal = {Computer Science and Information Systems},
     publisher = {mathdoc},
     volume = {17},
     number = {3},
     year = {2020},
     url = {http://geodesic.mathdoc.fr/item/CSIS_2020_17_3_a8/}
}
TY  - JOUR
AU  - Xindong You
AU  - Jiangwei Ma
AU  - Yuwen Zhang
AU  - Xueqiang Lv
AU  - Junmei Han
TI  - VDRF: Sensing the Defect Information to Risk Level of Vehicle Recall based on Bert Communication Model
JO  - Computer Science and Information Systems
PY  - 2020
VL  - 17
IS  - 3
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/CSIS_2020_17_3_a8/
ID  - CSIS_2020_17_3_a8
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%A Jiangwei Ma
%A Yuwen Zhang
%A Xueqiang Lv
%A Junmei Han
%T VDRF: Sensing the Defect Information to Risk Level of Vehicle Recall based on Bert Communication Model
%J Computer Science and Information Systems
%D 2020
%V 17
%N 3
%I mathdoc
%U http://geodesic.mathdoc.fr/item/CSIS_2020_17_3_a8/
%F CSIS_2020_17_3_a8
Xindong You; Jiangwei Ma; Yuwen Zhang; Xueqiang Lv; Junmei Han. VDRF: Sensing the Defect Information to Risk Level of Vehicle Recall based on Bert Communication Model. Computer Science and Information Systems, Tome 17 (2020) no. 3. http://geodesic.mathdoc.fr/item/CSIS_2020_17_3_a8/