CHANG Liang,SUN Wenping,ZHANG Weitao,et al.Review of tourism route planning[J].CAAI Transactions on Intelligent Systems,2019,14(1):82-92.[doi:10.11992/tis.201804005]





Review of tourism route planning
常亮 孙文平 张伟涛 宾辰忠 古天龙
桂林电子科技大学 广西可信软件重点实验室, 广西 桂林 541004
CHANG Liang SUN Wenping ZHANG Weitao BIN Chenzhong GU Tianlong
Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology, Guilin 541004, China
tourism route planninglocation-based servicetrajectory miningpersonalized recommendationcontext-awareorientation problemuser-generated dataall-for-one tourism
With the rapid development of tourism and surge in user sharing, information overload in tourism has become an increasing problem. Currently, the key issue in tourism route planning is how to help tourists to develop personalized travel routes and enhance their travel experiences. In this paper, we first provide a formal definition of the tourism route planning problem.. Then, we sort the methods used to solve this problem into two categories, i.e., those based on exact mathematical modeling and those based on user-generated content. We then present a detailed survey of the key technologies and difficulties of these methods. Lastly, we propose an overall framework for the tourism route planning system, analyze the key difficulties of the system, provide theoretical support for the study of tourism route planning, and suggest a future research direction.


[1] 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
[2] GAVALAS D, KONSTANTOPOULOS C, MASTAKAS K, et al. A survey on algorithmic approaches for solving tourist trip design problems[J]. Journal of heuristics, 2014, 20(3):291-328.
[3] ZHOU Xiaolu, WANG Mingshu, LI Dongying. From stay to play-a travel planning tool based on crowdsourcing user-generated contents[J]. Applied geography, 2017, 78:1-11.
[4] ABBASPOUR R A, SAMADZADEGAN F. Time-dependent personal tour planning and scheduling in metropolises[J]. Expert systems with applications, 2011, 38(10):12439-12452.
[5] GAVALAS D, KASAPAKIS V, KONSTANTOPOULOS C, et al. A personalized multimodal tourist tour planner[C]//Proceedings of the 13th International Conference on Mobile and Ubiquitous Multimedia. Melbourne, Australia, 2014:73-80.
[6] BAO Jie, ZHENG Yu, WILKIE D, et al. Recommendations in location-based social networks:a survey[J]. GeoInformatica, 2015, 19(3):525-565.
[7] ZHENG Bolong, SU Han, ZHENG Kai, et al. Landmark-based route recommendation with crowd intelligence[J]. Data science and engineering, 2016, 1(2):86-100.
[8] SOUFFRIAU W, VANSTEENWEGEN P, VERTOMMEN J, et al. A personalized tourist trip design algorithm for mobile tourist guides[J]. Applied artificial intelligence, 2008, 22(10):964-985.
[9] GUNAWAN A, LAU H C, VANSTEENWEGEN P, et al. Well-tuned algorithms for the team orienteering problem with time windows[J]. Journal of the operational research society, 2017, 68(8):861-876.
[10] GUNAWAN A, LAU H C, LU Kun. An iterated local search algorithm for solving the orienteering problem with time windows[M]//OCHOA G, CHICANO F. Evolutionary Computation in Combinatorial Optimization. Cham:Springer, 2015:61-73.
[11] GUNAWAN A, LAU H C, LU Kun. SAILS:hybrid algorithm for the team orienteering problem with time windows[C]//Proceedings of the 7th Multidisciplinary International Scheduling Conference. Prague, Czech Republic, 2015:276-295.
[12] VERBEECK C, SÖRENSEN K, AGHEZZAF E H, et al. A fast solution method for the time-dependent orienteering problem[J]. European journal of operational research, 2014, 236(2):419-432.
[13] SCHILDE M, DOERNER K F, HARTL R F, et al. Metaheuristics for the bi-objective orienteering problem[J]. Swarm intelligence, 2009, 3(3):179-201.
[14] LU Ying, SHAHABI C. An arc orienteering algorithm to find the most scenic path on a large-scale road network[C]//Proceedings of the 23th SIGSPATIAL International Conference on Advances in Geographic Information Systems. Seattle, Washington, 2015:51-62.
[15] LU Ying, JOSSE G, EMRICH T, et al. Scenic routes now:efficiently solving the time-dependent arc orienteering problem[C]//Proceedings of 2017 ACM Conference on Information and Knowledge Management. Singapore, 2017:487-496.
[16] LU Yongliang, BENLIC U, WU Qinghua. A memetic algorithm for the orienteering problem with mandatory visits and exclusionary constraints[J]. European journal of operational research, 2018, 268(1):54-69.
[17] GAO Huiji, TANG Jiliang, HU Xia, et al. Exploring temporal effects for location recommendation on location-based social networks[C]//Proceedings of the 7th ACM Conference on Recommender Systems. Hong Kong, China, 2013:93-100.
[18] XU Ying, HU Tao, LI Ying. A travel route recommendation algorithm with personal preference[C]//Proceedings of the 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery. Changsha, China, 2016:390-396.
[19] 柯良军, 章鹤, 尚可, 等. 一类求解带时间窗的团队定向问题的改进蚁群算法[J]. 计算机科学, 2012, 39(4):214-216 KE Liangjun, ZHANG He, SHANG Ke, et al. Improved ant colony optimization approach for the team orienteering problem with time windows[J]. Computer science, 2012, 39(4):214-216
[20] LIN S W, YU V F. A simulated annealing heuristic for the team orienteering problem with time windows[J]. European journal of operational research, 2012, 217(1):94-107.
[21] GARCIA A, VANSTEENWEGEN P, ARBELAITZ O, et al. Integrating public transportation in personalised electronic tourist guides[J]. Computers and operations research, 2013, 40(3):758-774.
[22] LUO Zhixing, CHEANG B, LIM A, et al. An adaptive ejection pool with toggle-rule diversification approach for the capacitated team orienteering problem[J]. European journal of operational research, 2013, 229(3):673-682.
[23] LI Zhenping, HU Xianman. The team orienteering problem with capacity constraint and time window[C]//Proceedings of the 10th International Symposium on Operations Research and Its Applications. Dunhuang, China, 2011:157-163.
[24] HJALAGER A M. 100 Innovations that transformed tourism[J]. Journal of travel research, 2015, 54(1):3-21.
[25] MURPHY H C, CHEN Mengmei, COSSUTTA M. An investigation of multiple devices and information sources used in the hotel booking process[J]. Tourism management, 2016, 52:44-51.
[26] BANERJEE S, CHUA A Y K. In search of patterns among travellers’ hotel ratings in TripAdvisor[J]. Tourism management, 2016, 53:125-131.
[27] ZHOU Xiaohu, XU Chen, KIMMONS B. Detecting tourism destinations using scalable geospatial analysis based on cloud computing platform[J]. Computers, environment and urban systems, 2015, 54:144-153.
[28] 郭黎敏, 高需, 武斌, 等. 基于停留时间的语义行为模式挖掘[J]. 计算机研究与发展, 2017, 54(1):111-122 GUO Limin, GAO Xu, WU Bin, et al,. Discovering common behavior using staying duration on semantic trajectory[J]. Journal of computer research and development, 2017, 54(1):111-122
[29] 高强, 张凤荔, 王瑞锦, 等. 轨迹大数据:数据处理关键技术研究综述[J]. 软件学报, 2017, 28(4):959-992 GAO Qiang, ZHANG Fengli, WANG Ruijin, et al. Trajectory big data:a review of key technologies in data processing[J]. Journal of software, 2017, 28(4):959-992
[30] 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.
[31] SUN Yeran, FAN Hongchao, BAKILLAH M, et al. Road-based travel recommendation using geo-tagged images[J]. Computers, environment and urban systems, 2015, 53:110-122.
[32] WEI Lingyin, ZHENG Yu, PENG W C. Constructing popular routes from uncertain trajectories[C]//Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Beijing, China, 2012:195-203.
[33] TAI C H, YANG Denian, LIN L T, et al. Recommending personalized scenic itinerarywith geo-tagged photos[C]//Proceedings of 2008 IEEE International Conference on Multimedia and Expo. Hannover, Germany, 2008:1209-1212.
[34] LU X, WANG C, YANG J M, et al. Photo2Trip:generating travel routes from geo-tagged photos for trip planning[C]//Proceedings of the 18th International Conference on Multimedia. Florence, Italy, 2010:143-152.
[35] KURASHIMA T, IWATA T, IRIE G, et al. Travel route recommendation using geotagged photos[J]. Knowledge and information systems, 2013, 37(1):37-60.
[36] KURASHIMA T, IWATA T, IRIE G, et al. Travel route recommendation using geotags in photo sharing sites[C]//Proceedings of the 19th ACM International Conference on Information and Knowledge Management. Toronto, Canada, 2010:579-588.
[37] ARAIN Q A, MEMON H, MEMON I, et al. Intelligent travel information platform based on location base services to predict user travel behavior from user-generated GPS traces[J]. International journal of computers and applications, 2017, 39(3):155-168.
[38] HUANG Haosheng. Context-aware location recommendation using geotagged photos in social media[J]. International journal of geo-information, 2016, 5(11):195.
[39] 宋晓宇, 许鸿斐, 孙焕良, 等. 基于签到数据的短时间体验式路线搜索[J]. 计算机学报, 2013, 36(8):1693-1703 SONG Xiaoyu, XU Hongfei, SUN Huanliang, et al. Short-term experience route search based on check-in data[J]. Chinese journal of computers, 2013, 36(8):1693-1703
[40] 宋晓宇, 闫玉奇, 孙焕良, 等. 基于签到数据的群体旅游路线推荐[J]. 计算机科学与探索, 2015, 9(1):51-62 SONG Xiaoyu, YAN Yuqi, SUN Huanliang, et al. Group trip recommendation based on check-in Data[J]. Journal of frontiers of computer science and technology, 2015, 9(1):51-62
[41] CHO E, MYERS S A, LESKOVEC J. Friendship and mobility:user movement in location-based social networks[C]//Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. San Diego, CA, USA, 2011:1082-1090.
[42] RAHIMI S M, WANG Xin. Location Recommendation based on periodicity of human activities and location categories[M]//PEI Jian, TSENG V S, CAO Longbing, et al. Advances in Knowledge Discovery and Data Mining. Berlin, Heidelberg:Springer, 2013:377–389.
[43] GUO Tong, GUO Bin, OUYANG YI, et al. CrowdTravel:scenic spot profiling by using heterogeneous crowdsourced data[J]. Journal of ambient intelligence and humanized computing, 2017(5):1-10.
[44] CHEN Chao, CHEN Xia, WANG Zhu, et al. ScenicPlanner:planning scenic travel routes leveraging heterogeneous user-generated digital footprints[J]. Frontiers of computer science, 2017, 11(1):61-74.
[45] CHEN Dawei, ONG C S, XIE Lexing. Learning points and routes to recommend trajectories[C]//Proceedings of the 25th ACM International on Conference on Information and Knowledge Management. Indianapolis, USA, 2016:2227-2232.
[46] LU E H C, CHEN C Y, TSENG V S. Personalized trip recommendation with multiple constraints by mining user check-in behaviors[C]//Proceedings of 20th International Conference on Advances in Geographic Information Systems. Redondo Beach, CA, USA, 2012:209-218.
[47] ZHENG Yu, ZHANG Lizhu, XIE Xing, et al. Mining interesting locations and travel sequences from GPS trajectories[C]//Proceedings of the 18th International Conference on World Wide Web. Madrid, Spain, 2009:791-800.
[48] KOU Feifei, DU Junping, LIN Zijian, et al. A semantic modeling method for social network short text based on spatial and temporal characteristics[J]. Journal of computational science, 2017.
[49] CHENG Xueqi, YAN Xiaohui, LAN Yanyan, et al. BTM:topic modeling over short texts[J]. IEEE transactions on knowledge and data engineering, 2014, 26(12):2928-2941.


更新日期/Last Update: 1900-01-01