| 旅游推荐系统研究综述 |
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| 引用本文： | 常亮,曹玉婷,孙文平,张伟涛,陈君同.旅游推荐系统研究综述[J].计算机科学,2017,44(10):1-6. |
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| 作者姓名： | 常亮 曹玉婷 孙文平 张伟涛 陈君同 |
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| 作者单位： | 桂林电子科技大学广西可信软件重点实验室 桂林541004,桂林电子科技大学广西可信软件重点实验室 桂林541004,桂林电子科技大学广西可信软件重点实验室 桂林541004,桂林电子科技大学广西可信软件重点实验室 桂林541004,桂林电子科技大学广西可信软件重点实验室 桂林541004 |
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| 基金项目： | 本文受国家自然科学基金(61363030,6,U1501252),广西自然科学基金(2015GXNSFAA139285,6GXNSFDA380006),广西信息科学实验中心(LD16058X)资助 |
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| 摘 要： | 为用户提供个性化推荐服务并提高推荐的准确度和用户满意度,是当前旅游推荐系统的主要研究任务。文中分析了旅游推荐系统与传统推荐系统的异同点,并从基于内容的推荐、基于协同过滤的推荐、基于知识的推荐、基于人口统计的推荐、混和型推荐以及基于位置感知的推荐共6个方面考查了旅游推荐的研究现状。在此基础上,给出了旅游推荐系统的一个总体框架。最后,总结分析了旅游推荐系统面临的6个重点和难点问题,并指出了下一步需要关注的研究方向。
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| 关 键 词： | 推荐技术 旅游推荐系统 协同过滤 |
| 收稿时间： | 2016/9/27 0:00:00 |
| 修稿时间： | 2017/2/15 0:00:00 |
Review on Tourism Recommendation System |
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| CHANG Liang,CAO Yu-ting,SUN Wen-ping,ZHANG Wei-tao and CHEN Jun-tong.Review on Tourism Recommendation System[J].Computer Science,2017,44(10):1-6. |
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| Authors: | CHANG Liang CAO Yu-ting SUN Wen-ping ZHANG Wei-tao and CHEN Jun-tong |
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| Affiliation: | Guangxi Key Laboratory of Trusted Software,Guilin University of Electronic Technology,Guilin 541004,China,Guangxi Key Laboratory of Trusted Software,Guilin University of Electronic Technology,Guilin 541004,China,Guangxi Key Laboratory of Trusted Software,Guilin University of Electronic Technology,Guilin 541004,China,Guangxi Key Laboratory of Trusted Software,Guilin University of Electronic Technology,Guilin 541004,China and Guangxi Key Laboratory of Trusted Software,Guilin University of Electronic Technology,Guilin 541004,China |
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| Abstract: | The main research task of current tourism recommendation system is to provide personal recommendation serves for users and improve the accuracy of recommendations and the satisfaction of users.In this paper,the similarities and differences between tourism recommender system and traditional recommender systemare were analyzed.And the research status of tourism recommender technologies was investigated from six aspects,i.e.,recommendation based on content,recommendation based on collaborative-filtering,recommendation based on knowledge,recommendation based on demographics,hybrid recommendation and recommendation based on location-awareness.As a summary of these research works,a general framework for tourism recommender system was proposed.Finally,six key and difficult problems on tourism recommender systems were presented,and some research topics which might bring great progress to tourism recommender systems were emphasized. |
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| Keywords: | Recommender technology Tourism recommender system Collaboration-filtering |
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