[1]王少兵,吴升.采用在线评论的景点个性化推荐[J].华侨大学学报(自然科学版),2018,39(3):467-472.[doi:10.11830/ISSN.1000-5013.201709015]
 WANG Shaobing,WU Sheng.Attractions Personalized Recommendations Using Online Reviews[J].Journal of Huaqiao University(Natural Science),2018,39(3):467-472.[doi:10.11830/ISSN.1000-5013.201709015]
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采用在线评论的景点个性化推荐()
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《华侨大学学报(自然科学版)》[ISSN:1000-5013/CN:35-1079/N]

卷:
第39卷
期数:
2018年第3期
页码:
467-472
栏目:
出版日期:
2018-05-20

文章信息/Info

Title:
Attractions Personalized Recommendations Using Online Reviews
文章编号:
1000-5013(2018)03-0467-06
作者:
王少兵 吴升
福州大学 福建省空间信息工程研究中心, 福建 福州 350003
Author(s):
WANG Shaobing WU Sheng
Spatial Information Research Center of Fujian, Fuzhou University, Fuzhou 350003, China
关键词:
旅游网站 在线评论 情感分析 个性化推荐
Keywords:
travel sites online reviews sentiment analysis personalized recommendations
分类号:
TP391
DOI:
10.11830/ISSN.1000-5013.201709015
文献标志码:
A
摘要:
通过对旅游网站的景点评论进行情感分析,综合利用自然语言处理技术和领域本体构建技术,准确把握游客对旅游目的地的满意度和需求;将群体智慧和个人偏好有效地结合,为游客出行制定合理的个性化推荐策略.实验结果表明:所提出的推荐策略能够有效地将碎片化的游客评论数据转化为对其他游客出行地选择的辅助信息,提高了游客获取旅游知识的效率,真实地反映游客的旅游感受,为游客景点选择提供参考.
Abstract:
Through analyzing attractions online reviews of travel sites based on sentiment analysis, this paper comprehensively utilizes natural language processing technology and domain ontology construction technology, accurately grasps the tourist satisfaction and the demand for tourism destination, effectively combines the wisdom of crowds and personal preference, and sets reasonable personalized recommendation for tourists travel strategy. The experimental results show that the proposed strategy can effectively translate fragmented visitors review data into ancillary information of tourists traveling, improve the efficiency of the tourists to obtain knowledge, truly reflect the tourists feel, and provide the reference for tourist choosing attractions.

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备注/Memo

备注/Memo:
收稿日期: 2017-09-11
通信作者: 吴升(1972-),男,教授,博士,主要从事时空数据分析与可视化、信息共享与智慧政务、应急信息系统的研究.E-mail:ws0110@163.com.
基金项目: 国家政务大数据应用工程技术研究中心培育项目(2016L3007); 福建省科技创新平台建设项目(2015H2001)
更新日期/Last Update: 2018-05-20