Personalized Travel Recommendation Based on Sentiment-Aware Multimodal Topic Model

doi:10.1109/ACCESS.2019.2935155

	Personalized Travel Recommendation Based on Sentiment-Aware Multimodal Topic Model
	Shao, Xi 1,2; Tang, Guijin 1; Bao, Bing-Kun1
发表期刊	IEEE ACCESS
ISSN	2169-3536
	2019
卷号	7 页码:113043-113052
通讯作者	Shao, Xi(shaoxi@njupt.edu.cn)
摘要	In this paper, we try to solve the personalized travel recommendation problem by exploiting the multi-modal data available from the real world social media, and a probabilistic graph model so called Sentiment-aware Multi-modal Topic Model (SMTM) is proposed to mine the latent semantics of the multi-modal data on the online travel website. Distinguished from previous approaches, our proposed approach try to mine the topics from tourist and attraction domains separately for disclosing semantics for tourist topics and attraction themes. In addition, we analyze tourist's sentiments on attractions to further obtain the tourist's attitude over attractions and recommend the attraction with proper sentiment on the related attraction themes accordingly. Based on the proposed SMTM model, the documents in tourist domain and in attraction domain can be compared with each other after they were projected into the mutual topic space, and this latent space projection scheme can be further applied to two personalized traveling recommendations, that is, the single platform traveling recommendation and the inter-platform traveling recommendation. Evaluation results based on the real world online travel website have shown the improved performance of our method.
关键词	Tourism recommendation multi-modality topic model sentiment analysis
DOI	10.1109/ACCESS.2019.2935155
关键词[WOS]	TOURISM ; SYSTEMS
收录类别	SCI
语种	英语
资助项目	National Science Foundation of China[61872199] ; National Science Foundation of China[61872424] ; National Science Foundation of China[61772287] ; Key University Science Research Project of Jiangsu Province[18KJA510004] ; Nanjing University of Posts and Telecommunications Support Funding[NY218001] ; National Science Foundation of China[61872199] ; National Science Foundation of China[61872424] ; National Science Foundation of China[61772287] ; Key University Science Research Project of Jiangsu Province[18KJA510004] ; Nanjing University of Posts and Telecommunications Support Funding[NY218001]
项目资助者	National Science Foundation of China ; Key University Science Research Project of Jiangsu Province ; Nanjing University of Posts and Telecommunications Support Funding
WOS研究方向	Computer Science ; Engineering ; Telecommunications
WOS类目	Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS记录号	WOS:000483020700001
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
七大方向——子方向分类	多模态智能
引用统计	被引频次：13[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/27276
专题	多模态人工智能系统全国重点实验室_多媒体计算
通讯作者	Shao, Xi
作者单位	1.Nanjing Univ Posts & Telecommun, Coll Commun & Informat Engn, Nanjing 210003, Jiangsu, Peoples R China 2.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China
第一作者单位	模式识别国家重点实验室
通讯作者单位	模式识别国家重点实验室
推荐引用方式 GB/T 7714	Shao, Xi,Tang, Guijin,Bao, Bing-Kun. Personalized Travel Recommendation Based on Sentiment-Aware Multimodal Topic Model[J]. IEEE ACCESS,2019,7:113043-113052.
APA	Shao, Xi,Tang, Guijin,&Bao, Bing-Kun.(2019).Personalized Travel Recommendation Based on Sentiment-Aware Multimodal Topic Model.IEEE ACCESS,7,113043-113052.
MLA	Shao, Xi,et al."Personalized Travel Recommendation Based on Sentiment-Aware Multimodal Topic Model".IEEE ACCESS 7(2019):113043-113052.