[1]匡海丽,常亮,宾辰忠,等.上下文感知旅游推荐系统研究综述[J].智能系统学报,2019,14(4):611-618.[doi:10.11992/tis.201901013]
KUANG Haili,CHANG Liang,BIN Chenzhong,et al.Review of a context-aware travel recommendation system[J].CAAI Transactions on Intelligent Systems,2019,14(4):611-618.[doi:10.11992/tis.201901013]
点击复制
KUANG Haili,CHANG Liang,BIN Chenzhong,et al.Review of a context-aware travel recommendation system[J].CAAI Transactions on Intelligent Systems,2019,14(4):611-618.[doi:10.11992/tis.201901013]
上下文感知旅游推荐系统研究综述
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
14
期数:
2019年第4期
页码:
611-618
栏目:
综述
出版日期:
2019-07-02
- Title:
- Review of a context-aware travel recommendation system
- Keywords:
- context-aware; tourism recommendation system; recommendation based on location; social network; personalized recommendation; tourist attraction recommendation; travel route recommendation; travel package recommendation
- 分类号:
- TP301
- 摘要:
- 随着人们生活水平的提高，旅游已成为一项普遍的休闲活动，进而推动了旅游推荐方面技术的研究。与传统推荐系统相比，除了考虑游客和旅游产品的相关特征之外，旅游推荐系统的推荐质量在很大程度上受到位置、时间、天气、游客社交群体等上下文信息的影响。本文首先给出上下文感知旅游推荐系统的总体框架；然后对位置、时间、游客社会化网络和多维上下文等4类典型的上下文信息在旅游推荐系统中的应用进行了详细考察，并对综合应用各种上下文信息的旅游推荐系统进行了分析；从旅游推荐产品的角度对推荐系统进行分类考察；最后讨论了上下文感知旅游推荐系统目前面临的重点和难点问题，指出下一步的研究方向。
- Abstract:
- With improved living standards, tourism has become a common leisure activity that has promoted the research of tourism recommendation technologies. When compared with a traditional recommendation system, the quality the proposed system is considerably influenced by the contextual information, including the location, time, weather, and social groups of tourists, in addition to relevant characteristics of tourists and tourism products. In this study, we provide the overall framework of a context-aware tourism recommendation system. The application of four typical types of context information in the travel recommendation system, such as the location, time, visitor social network, and multidimensional context, is investigated in detail, and the tourism recommendation system that comprehensively applies various types of contextual information is analyzed. Further, the tourism recommendation system is classified and inspected from the perspective of the tourism recommendation products. Finally, key and difficult problems faced by the context-aware tourism recommendation system are discussed, and the future research direction is identified.
- 参考文献/References:
-
[1] DE PESSEMIER T, DHONDT J, MARTENS L. Hybrid group recommendations for a travel service[J]. Multimedia tools and applications, 2017, 76(2):2787-2811.
[2] ZIMBA B, CHIBUTA S, CHISANGA D, et al. Point of interest recommendation methods in location based social networks:traveling to a new geographical region[J]. arXiv:1711.09471, 2017.
[3] MAO Xueyu, MITRA S, SWAMINATHAN V. Feature selection for FM-based context-aware recommendation systems[C]//Proceedings of 2017 IEEE International Symposium on Multimedia (ISM). Taichung, China, 2017.
[4] 李慧, 马小平, 胡云, 等. 融合上下文信息的社会网络推荐系统[J]. 智能系统学报, 2015, 10(2):293-300 LI Hui, MA Xiaoping, HU Yun, et al. Social network recommendaton system mixing contex information[J]. CAAI transactions on intelligent systems, 2015, 10(2):293-300
[5] MIAO Dongchen, LANG Fei. A recommendation system based on text mining[C]//Proceedings of 2017 International Conference on Cyber-enabled Distributed Computing and Knowledge Discovery. Nanjing, China, 2017.
[6] FU Mingsheng, QU Hong, YI Zhang, et al. A novel deep learning-based collaborative filtering model for recommendation system[J]. IEEE transactions on cybernetics, 2019, 49(3):1084-1096.
[7] WANG Donghui, LIANG Yanchun, XU D, et al. A content-based recommender system for computer science publications[J]. Knowledge-based systems, 2018, 157:1-9.
[8] ZHANG Yongfeng, AI Qingyao, CHEN Xu, et al. Learning over knowledge-base embeddings for recommendation[J]. arXiv:1803.06540, 2018.
[9] ZHAO X W, GUO Yanwei, HE Yulan, et al. We know what you want to buy:a demographic-based system for product recommendation on microblogs[C]//Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, USA, 2014.
[10] 常亮, 曹玉婷, 孙文平, 等. 旅游推荐系统研究综述[J]. 计算机科学, 2017, 44(10):1-6 CHANG Liang, CAO Yuting, SUN Wenping, et al. Review on tourism recommendation system[J]. Computer science, 2017, 44(10):1-6
[11] 孟祥武, 刘树栋, 张玉洁, 等. 社会化推荐系统研究[J]. 软件学报, 2015, 26(6):1356-1372 MENG Xiangwu, LIU Shudong, ZHANG Yujie, et al. Research on social recommender systems[J]. Journal of software, 2015, 26(6):1356-1372
[12] 张玉洁, 杜雨露, 孟祥武. 组推荐系统及其应用研究[J]. 计算机学报, 2016, 39(4):745-764 ZHANG Yujie, DU Yulu, MENG Xiangwu. Research on group recommender systems and their applications[J]. Chinese journal of computers, 2016, 39(4):745-764
[13] VINH T D Q, PHAM T A N, CONG Gao, et al. Attention-based group recommendation[J]. arXiv:1804.04327, 2018.
[14] NOGUERA J M, BARRANCO M J, SEGURA R J, et al. A mobile 3D-GIS hybrid recommender system for tourism[J]. Information sciences, 2012, 215:37-52.
[15] 彭菲菲, 钱旭. 基于用户关注度的个性化新闻推荐系统[J]. 计算机应用研究, 2012, 29(3):1005-1007 PENG Feifei, QIAN Xu. Personalized recommendation system for news based on user concern[J]. Application research of computers, 2012, 29(3):1005-1007
[16] LI Xinyu, MI Zhongchun, ZHANG Zhenmei, et al. A location-aware recommender system for tourism mobile commerce[C]//Proceedings of the 2nd International Conference on Information Science and Engineering. Hangzhou, China, 2010:1709-1711.
[17] LIU Hailing, LI Junhuai, PENG Jun. A novel recommendation system for the personalized smart tourism route:design and implementation[C]//Proceedings of the 14th International Conference on Cognitive Informatics & Cognitive Computing. Beijing, China, 2015:291-296.
[18] 王青. 考虑季节情境因素的旅游景点主题模型及应用研究[D]. 南京:东南大学, 2017. WANG Qing. Research on topic model of tourist attraction considering seasonal context and its applications[D]. Nanjing:Southeast University, 2017.
[19] 李雅美, 王昌栋. 基于标签的个性化旅游推荐[J]. 中国科学技术大学学报, 2017, 47(7):547-555 LI Yamei, WANG Changdong. Tag-based personalized travel recommendation[J]. Journal of University of Science and Technology of China, 2017, 47(7):547-555
[20] 卢露. 基于时间感知的地点推荐算法[J]. 计算机工程与科学, 2016, 38(3):590-594 LU Lu. A time-aware based location recommendation algorithm[J]. Computer engineering & science, 2016, 38(3):590-594
[21] ZHANG Jiadong, CHOW C Y. TICRec:a probabilistic framework to utilize temporal influence correlations for time-aware location recommendations[J]. IEEE transactions on services computing, 2016, 9(4):633-646.
[22] RAVI L, VAIRAVASUNDARAM S. A collaborative location based travel recommendation system through enhanced rating prediction for the group of users[J]. Computational intelligence and neuroscience, 2016:1291358.
[23] CENAMOR I, DE LA ROSA T, Nú?EZ S, et al. Planning for tourism routes using social networks[J]. Expert systems with applications, 2017, 69:1-9.
[24] CHRISTENSEN I, SCHIAFFINO S, ARMENTANO M. Social group recommendation in the tourism domain[J]. Journal of intelligent information systems, 2016, 47(2):209-231.
[25] 潘一腾, 何发智, 于海平. 一种基于信任关系隐含相似度的社会化推荐算法[J]. 计算机学报, 2018, 41(1):65-81 PAN Yiteng, HE Fazhi, YU Haiping. Social recommendation algorithm using implicit similarity in trust[J]. Chinese journal of computers, 2018, 41(1):65-81
[26] YAO Lina, SHENG Q Z, WANG Xianzhi, et al. Collaborative location recommendation by integrating multi-dimensional contextual information[J]. ACM transactions on internet technology, 2017, 18(3):32.
[27] 任星怡, 宋美娜, 宋俊德. 基于用户签到行为的兴趣点推荐[J]. 计算机学报, 2017, 40(1):28-51 REN Xingyi, SONG Meina, SONG Junde. Point-of-interest recommendation based on the user check-in behavior[J]. Chinese journal of computers, 2017, 40(1):28-51
[28] MEEHAN K, LUNNEY T, CURRAN K, et al. Aggregating social media data with temporal and environmental context for recommendation in a mobile tour guide system[J]. Journal of hospitality and tourism technology, 2016, 7(3):281-299.
[29] 赵海燕, 骆金, 陈庆奎. 时间与位置感知的活动个性化推荐方法[J]. 计算机工程, 2018, 44(4):218-224 ZHAO Haiyan, LUO Jin, CHEN Qingkui. Time and location-aware activity personalized recommendation method[J]. Computer engineering, 2018, 44(4):218-224
[30] GAO Huiji, TANG Jiliang, HU Xia, et al. Content-aware point of interest recommendation on location-based social networks[C]//Proceedings of the Twenty-Ninth AAAI conference on artificial intelligence. Austin, USA, 2015:1721-1727.
[31] DEBNATH M, TRIPATHI P K, ELMASRI R. Preference-aware successive POI recommendation with spatial and temporal influence[C]//Proceedings of the 8th International Conference on Social Informatics. Bellevue, USA, 2016.
[32] CHEN Xi, ZHOU Liqing. Design and implementation of an intelligent system for tourist routes recommendation based on Hadoop[C]//Proceedings of the 6th IEEE International Conference on Software Engineering and Service Science. Beijing, China, 2015:774-778.
[33] YU Zhiwen, XU Huang, YANG Zhe, et al. Personalized travel package with multi-point-of-interest recommendation based on crowdsourced user footprints[J]. IEEE transactions on human-machine systems, 2016, 46(1):151-158.
[34] DIPALI J, PRAGATI S, PRATIK U, et al. Travel package recommendation system based on package locations and rating[J]. International journal of computer applications, 2017, 179(8):1-3.
[35] AYATA D, YASLAN Y, KAMASAK M E. Emotion based music recommendation system using wearable physiological sensors[J]. IEEE transactions on consumer electronics, 2018, 64(2):196-203.
- 相似文献/References:
-
[1]常亮,孙文平,张伟涛,等.旅游路线规划研究综述[J].智能系统学报,2019,14(1):82.[doi:10.11992/tis.201804005]
CHANG Liang,SUN Wenping,ZHANG Weitao,et al.Review of tourism route planning[J].CAAI Transactions on Intelligent Systems,2019,14():82.[doi:10.11992/tis.201804005]
备注/Memo
收稿日期:2019-01-18。
基金项目:国家自然科学基金项目（U1711263，U1811264，U1501252，61572146）；广西创新驱动重大专项项目（AA17202024）；桂林电子科技大学研究生教育创新计划资助项目（2018YJCX52）；广西自然科学基金项目（2016GXNSFDA380006，AC16380122）；广西信息科学实验中心平台建设项目（PT1601）；广西高校中青年教师基础能力提升项目（2018KYD203）；广西可信软件重点实验资助课题（KX201729）.
作者简介:匡海丽,女,1995年生,硕士研究生,主要研究方向为个性化推荐、人工智能。主持桂林电子科技大学研究生教育创新计划项目1项;常亮,男,1980年生,教授,博士,中国计算机学会高级会员,主要研究方向为数据与知识工程、形式化方法、智能系统。主持国家自然科学基金项目1项,广西自然科学基金项目1项。发表学术论文70余篇,被SCI、EI收录60余篇;宾辰忠,男,1979年生,博士研究生,讲师,主要研究方向为数据挖掘、智能推荐。主持广西高校中青年教师基础能力提升项目1项。
通讯作者:宾辰忠.E-mail:binchenzhong@guet.edu.cn
更新日期/Last Update:
2019-08-25