计算机工程与应用2024，Vol.60Issue(8)：56-68,13.DOI:10.3778/j.issn.1002-8331.2309-0030
监督式主题模型及其应用综述
Review of Supervised Topic Models and Applications
摘要
Abstract
Topic model is a data mining method that can automatically extract potential patterns or topics from a large number of files or data,and assign the corresponding data to the corresponding patterns or topics.Topic models have been widely used in the fields of text clustering or classification,topic extraction,topic evolution,sentiment analysis and summary.The difference between a supervised topic model and an unsupervised topic model is whether it relies on annota-tion information.In recent years,supervised topic model has gradually emerged in data mining tasks,which makes more and more tasks tend to adopt supervised method for optimization.Firstly,the content of supervised topic model is presented,and the commonly used data sets and evaluation indicators are introduced.Secondly,from the perspective of model and application,different types of supervised topic models are analyzed in depth.Finally,the challenges facing the current research of thematic models are described,and the future research direction of supervised thematic models is prospected.关键词
数据挖掘/监督式主题模型/主题预测/主题演变Key words
data mining/supervised topic model/topic prediction/topic evolution分类
信息技术与安全科学引用本文复制引用
王振彪,徐贞顺,刘纳,张文豪,唐增金,王正安..监督式主题模型及其应用综述[J].计算机工程与应用,2024,60(8):56-68,13.基金项目
宁夏自然科学基金(2021AAC03217,2021AAC03224). （2021AAC03217,2021AAC03224）
