Discovering author interest evolution in order-sensitive and Semantic-aware topic modeling

doi:10.1016/j.ins.2019.02.040

CORC > 上海财经大学 > 上海财经大学

	Discovering author interest evolution in order-sensitive and Semantic-aware topic modeling
	Yang, Min 1; Qu, Qiang 1; Chen, Xiaojun 2; Tu, Wenting 3; Shen, Ying 4; Zhu, Jia 5
刊名	INFORMATION SCIENCES
	2019-06
卷号	486 页码:271-286
关键词	Topic model Dynamic author topic model Ordering-sensitive Semantic-aware
ISSN号	0020-0255
DOI	10.1016/j.ins.2019.02.040
英文摘要	Modeling the interests of authors over time from documents has important applications in broad applications such as recommendation systems, authorship identification and opinion extraction. In this paper, we propose an Ordering-sensitive and Semantic-aware Dynamic Author Topic Model (OSDATM), which monitors the evolution of author interest in timestamped documents. The model further uses the discovered author interest information to discover better topics. Unlike traditional topic models, OSDATM is sensitive to the ordering of words, thus it extracts more information from the semantic meaning of the context. The experimental results show that OSDATM learns better topics than state-of-the-art topic models. In addition, the dynamic interests of authors that the OSDATM model discovers are interpretable and consistent with the truth. (C) 2019 Published by Elsevier Inc.
WOS研究方向	Computer Science
语种	英语
出版者	ELSEVIER SCIENCE INC
WOS记录号	WOS:000464301300019
内容类型	期刊论文
源URL	[http://10.2.47.112/handle/2XS4QKH4/247]
专题	上海财经大学
通讯作者	Chen, Xiaojun
作者单位	1.Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen, Peoples R China; 2.Shenzhen Univ, Coll Comp Sci & Software, Shenzhen, Peoples R China; 3.Shanghai Univ Finance & Econ, Dept Comp Sci, Shanghai, Peoples R China; 4.Peking Univ, Shenzhen Grad Sch, Sch Elect & Comp Engn, Shenzhen, Peoples R China; 5.South China Normal Univ, Sch Comp Sci, Guangzhou, Guangdong, Peoples R China
推荐引用方式 GB/T 7714	Yang, Min,Qu, Qiang,Chen, Xiaojun,et al. Discovering author interest evolution in order-sensitive and Semantic-aware topic modeling[J]. INFORMATION SCIENCES,2019,486:271-286.
APA	Yang, Min,Qu, Qiang,Chen, Xiaojun,Tu, Wenting,Shen, Ying,&Zhu, Jia.(2019).Discovering author interest evolution in order-sensitive and Semantic-aware topic modeling.INFORMATION SCIENCES,486,271-286.
MLA	Yang, Min,et al."Discovering author interest evolution in order-sensitive and Semantic-aware topic modeling".INFORMATION SCIENCES 486(2019):271-286.