典型文献
A Novel User Behavior Prediction Model Based on Automatic Annotated Behavior Recognition in Smart Home Systems
文献摘要:
User behavior prediction has become a core element to Internet of Things (IoT) and received promising attention in the related fields. Many ex-isting IoT systems (e.g. smart home systems) have been deployed various sensors and the user's behavior can be predicted through the sensor data. However, most of the existing sensor-based systems use the an-notated behavior data which requires human interven-tion to achieve the behavior prediction. Therefore, it is a challenge to provide an automatic behavior predic-tion model based on the original sensor data. To solve the problem, this paper proposed a novel automatic annotated user behavior prediction (AAUBP) model. The proposed AAUBP model combined the Discontin-uous Solving Order Sequence Mining (DVSM) behav-ior recognition model and behavior prediction model based on the Long Short Term Memory (LSTM) net-work. To evaluate the model, we performed several experiments on a real-world dataset tuning the param-eters. The results showed that the AAUBP model can effectively recognize behaviors and had a good perfor-mance for behavior prediction.
文献关键词:
中图分类号:
作者姓名:
Ningbo Zhang;Yajie Yan;Xuzhen Zhu;Jing Wang
作者机构:
Key Laboratory of Universal Wireless Communications,Ministry of Education,Beijing University of Posts and Telecommunications,Beijing 100876,China;School of Artificial Intelligence,Beijing Normal University,Beijing 100875,China
文献出处:
引用格式:
[1]Ningbo Zhang;Yajie Yan;Xuzhen Zhu;Jing Wang-.A Novel User Behavior Prediction Model Based on Automatic Annotated Behavior Recognition in Smart Home Systems)[J].中国通信(英文版),2022(09):116-132
A类:
Annotated,notated,AAUBP,Discontin,DVSM
B类:
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AB值:
0.531898
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