NEUTags Classification System for Zhihu Questions Tagging Task

摘要：

　　In the multi-label classification task(Automatic Tagging of Zhihu Questions),we present a classification system which includes five processes.Firstly,we use a preprocessing step to solve the problem that there is too much noise in the training dataset.Secondly,we choose several neural network models which proved effective in text classification task.Then we introduce kmax pooling structure to these models to fit this task.Thirdly,in order to obtain a better performance in ensemble process,we use an experiment-designing process to obtain classification results that are not similar to each other and all achieve relatively high scores.Fourthly,we use an ensemble process.Finally,we propose a method to estimate how many labels should be chosen.With these processes,our F1 score achieves 0.5194,which ranked No.3.

关键词： Multi-label classification Question tagging Ensemble learning

作者: Yuejia Xiang HuiZheng Wang Duo Ji Zheyang Zhang Jingbo Zhu

作者单位: Natural Language Processing Laboratory,Northeastern University,Shenyang,China Criminal Investigation Police University of China,Shenyang,China

会议类型: 国际会议

会议名称: 2018自然语言处理与中文计算国际会议(NLPCC2018)

会议地点: 呼和浩特

会议语种:英文

页码: 279-288

在线出版日期: 2018-08-26（万方平台首次上网日期，不代表论文的发表时间）