%0 Journal Article
%A GAO Peng-fei
%A LIANG Yue
%A LIU Shao-hua
%A MA Ying-long
%A LI Jian-gui
%T A Hierarchical Category Embedding Based Approach for Fault Classification of Power ICT System
%D 
%R 10.13190/j.jbupt.2020-271
%J Journal of Beijing University of Posts and Telecommunications
%P 34-40
%V 44
%N 4
%X To solve the low classification accuracy oreven misclassification issue in fault diagnosis, a text classification method based on hierarchical category embedding is proposed in information and communication technology (ICT) customer service systems. First, a hierarchical label system is constructed for the failure data in power ICT systems based on the textual data of the work orders.Then, hierarchical deep pyramid convolutional neural networks (HDPCNN) and hierarchical disconnected recurrent neural networks are proposed, which adopt hierarchical category embedding technique for level-by-level fault type classification. The experimental results show that the hierarchical text classification algorithm HDPCNN has the best classification accuracy, which can provide efficient and accurate services for fault type recognition.
%U https://journal.bupt.edu.cn/EN/10.13190/j.jbupt.2020-271