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第1期 YOCHUM Phatpicha,等:基于位置和开放链接数据的旅游推荐系统综述 ·31· 15-23 ages[J].Computers,environment and urban systems, [17]GAO Rong,LI Jing,LI Xuefei,et al.STSCR:exploring 2015,53:110-122 spatial-temporal sequential influence and social informa- [29]LIM K H,CHAN J,LECKIE C,et al.Personalized trip tion for location recommendation[J].Neurocomputing, recommendation for tourists based on user interests. 2018.319:118-133 points of interest visit durations and visit recency[J]. [18]WEN Yuting,YEO J,PENG W,et al.Efficient keyword- Knowledge and information systems,2018,54(2): aware representative travel route recommendation[J]. 375-406. 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[40]KESORN K.JURAPHANTHONG W.SALAIWARAK- Road-based travel recommendation using geo-tagged im- UL A.Personalized attraction recommendation system for15–23. GAO Rong, LI Jing, LI Xuefei, et al. STSCR: exploring spatial-temporal sequential influence and social informa￾tion for location recommendation[J]. Neurocomputing, 2018, 319: 118–133. [17] WEN Yuting, YEO J, PENG W, et al. Efficient keyword￾aware representative travel route recommendation[J]. IEEE transactions on knowledge and data engineering, 2017, 29(8): 1639–1652. [18] LU E H C, FANG S H, TSENG V S. Integrating tourist packages and tourist attractions for personalized trip plan￾ning based on travel constraints[J]. GeoInformatica, 2016, 20(4): 741–763. [19] HANG Lei, KANG S H, JIN Wenquan, et al. Design and implementation of an optimal travel route recommender system on big data for tourists in Jeju[J]. Processes, 2018, 6(8): 133. [20] WÖRNDL W, HEFELE A, HERZOG D. Recommending a sequence of interesting places for tourist trips[J]. In￾formation technology & tourism, 2017, 17(1): 31–54. [21] JIANG Shuhui, QIAN Xueming, MEI Tao, et al. Person￾alized travel sequence recommendation on multi-source big social media[J]. IEEE transactions on big data, 2016, 2(1): 43–56. [22] CUI Ge, LUO Jun, WANG Xin. Personalized travel route recommendation using collaborative filtering based on GPS trajectories[J]. International journal of digital earth, 2018, 11(3): 284–307. [23] DUAN Zongtao, TANG Lei, GONG Xuehui, et al. Per￾sonalized service recommendations for travel using tra￾jectory pattern discovery[J]. International journal of dis￾tributed sensor networks, 2018, 14(3). [24] CHEN Dawei, ONG C S, XIE Lexing. Learning points and routes to recommend trajectories[C]//Proceedings of the 25th ACM International on Conference on Informa￾tion and Knowledge Management. Indianapolis, IN, USA, 2016. [25] ZHU Liang, XU Changqiao, GUAN Jianfeng, et al. SEM￾PPA: a semantical pattern and preference-aware service mining method for personalized point of interest recom￾mendation[J]. Journal of network and computer applica￾tions, 2017, 82: 35–46. [26] HSIEH H P, LI Chengte, LIN Shoude. Measuring and re￾commending time-sensitive routes from location-based data[J]. ACM transactions on intelligent systems and technology, 2014, 5(3): 45. [27] SUN Yeran, FAN Hongchao, BAKILLAH M, et al. Road-based travel recommendation using geo-tagged im- [28] ages[J]. Computers, environment and urban systems, 2015, 53: 110–122. LIM K H, CHAN J, LECKIE C, et al. Personalized trip recommendation for tourists based on user interests, points of interest visit durations and visit recency[J]. Knowledge and information systems, 2018, 54(2): 375–406. [29] HAN J, LEE H. Adaptive landmark recommendations for travel planning: personalizing and clustering landmarks using geo-tagged social media[J]. Pervasive and mobile computing, 2015, 18: 4–17. [30] KAUSHIK S, TIWARI S, AGARWAL C, et al. Ubiquit￾ous crowdsourcing model for location recommender sys￾tem[J]. Journal of computers, 2016, 11(6): 463–471. [31] YU Yaxin, ZHAO Yuhai, YU Ge, et al. Mining coterie patterns from Instagram photo trajectories for recom￾mending popular travel routes[J]. Frontiers of computer science, 2017, 11(6): 1007–1022. [32] WANG Xiangyu, ZHAO Yiliang, NIE Liqiang, et al. Se￾mantic-based location recommendation with multimodal venue semantics[J]. IEEE transactions on multimedia, 2015, 17(3): 409–419. [33] ARAIN Q A, MEMON H, MEMON I, et al. Intelligent travel information platform based on location base ser￾vices to predict user travel behavior from user-generated GPS traces[J]. International journal of computers and ap￾plications, 2017, 39(3): 155–168. [34] PÁLOVICS R, SZALAI P, PAP J, et al. Location-aware online learning for top-k recommendation[J]. Pervasive and mobile computing, 2017, 38: 490–504. [35] SMIRNOV A V, KASHEVNIK A M, PONOMAREV A. Context-based infomobility system for cultural heritage recommendation: Tourist Assistant—TAIS[J]. Personal and ubiquitous computing, 2017, 21(2): 297–311. [36] SHI Lin, LIN Feiyu, YANG Tianchu, et al. Context-based ontology-driven recommendation strategies for tourism in ubiquitous computing[J]. Wireless personal communica￾tions, 2014, 76(4): 731–745. [37] VOLKOVA L, YAGUNOVA E, PRONOZA E, et al. Re￾commender system for tourist itineraries based on aspects extraction from reviews corpora[J]. Polibits, 2018, 57: 81–88. [38] FERRARO P, LO RE G. Designing ontology-driven re￾commender systems for tourism[M]//GAGLIO S, LO RE G. Advances onto the Internet of Things. Cham, Ger￾many: Springer, 2014: 339−352. [39] KESORN K, JURAPHANTHONG W, SALAIWARAK￾UL A. Personalized attraction recommendation system for [40] 第 1 期 YOCHUM Phatpicha,等:基于位置和开放链接数据的旅游推荐系统综述 ·31·
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