WiseTag:An Ensemble Method for Multi-label Topic Classification

摘要：

　　Multi-label topic classification aims to assign one or more relevant topic labels to a text.This paper presents the WiseTag system,which performs multi-label topic classification based on an ensemble of four single models,namely a KNN-based model,an Information Gainbased model,a Keyword Matching-based model and a Deep Learningbased model.These single models are carefully designed so that they are diverse enough to improve the performance of the ensemble model.In the NLPCC 2018 shared task 6 “Automatic Tagging of Zhihu Questions,the proposed WiseTag system achieves an F1 score of 0.4863 on the test set,and ranks no.4 among all the teams.

关键词： Topic classification Tagging Multi-label

作者: Guanqing Liang Hsiaohsien Kao Cane Wing-Ki Leung Chao He

作者单位: Wisers AI Lab,Wisers Information Limited,Wan Chai,Hong Kong

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: 479-489

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）