Skip to main content
SpringerLink
Log in

Tour recommendation and trip planning using location-based social media: a survey

  • Survey Paper
  • Published:
Knowledge and Information Systems Aims and scope Submit manuscript

Abstract

Tourism is both an important industry and popular leisure activity undertaken by millions around the world. One important task for tourists is to plan and schedule tour itineraries that comprise multiple captivating Points-of-Interests based on the unique interest preferences of the tourist. The complex task of tour itinerary recommendation is further complicated by the need to incorporate various real-life constraints such as limited time for touring, uncertain traffic conditions, inclement weather, group travel, queuing times and crowdedness. In this survey, we conduct a comprehensive literature review of studies on tour itinerary recommendation and present a general taxonomy for touring-related research. We discuss the entire process of tour itinerary recommendation research including: (i) data collection and types of datasets; (ii) problem formulations and proposed algorithms/systems for individual travellers, groups of tourists and various real-life considerations; (iii) evaluation methodologies for comparing tour itinerary recommendation algorithms; and (iv) future directions and open problems in tour itinerary recommendation research.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Retrieved from [29]

Fig. 4

Retrieved from [106] (color figure online)

Fig. 5

Retrieved from [70]

Similar content being viewed by others

References

  1. Amer-Yahia S, Roy SB, Chawlat A, Das G, Yu C (2009) Group recommendation: semantics and efficiency. In: Proc. of VLDB’09, pp 754–765

  2. Anagnostopoulos A, Atassi R, Becchetti L, Fazzone A, Silvestri F (2016) Tour recommendation for groups. Data Min Knowl Discov 31:1–32

    MathSciNet  MATH  Google Scholar 

  3. Ardissono L, Goy A, Petrone G, Segnan M, Torasso P (2003) Intrigue: personalized recommendation of tourist attractions for desktop and hand held devices. App Artif Intell 17(8–9):687–714

    Article  Google Scholar 

  4. Baeza-Yates R, Ribeiro-Neto B (1999) Modern information retrieval. Addison-Wesley, Boston

    Google Scholar 

  5. Bao J, Yu Zheng DW, Mokbel M (2015) Recommendations in location-based social networks: a survey. GeoInformatica 19(3):525–565

    Article  Google Scholar 

  6. Baraglia R, Muntean CI, Nardini FM, Silvestri F (2013) Learnext: learning to predict tourists movements. In: Proc. of CIKM’13, pp 751–756

  7. Benouaret I, Lenne D (2016) A composite recommendation system for planning tourist visits. In Proc. of WI’16, pp 626–631

  8. Benouaret I, Lenne D (2016) A package recommendation framework for trip planning activities. In: Proc. of RecSys’16, pp 203–206

  9. Bolzoni P, Helmer S, Wellenzohn K, Gamper J, Andritsos P (2014) Efficient itinerary planning with category constraints. In: Proc. of SIGSPATIAL’14, pp 203–212

  10. Boratto L, Carta S (2011) State-of-the-art in group recommendation and new approaches for automatic identification of groups. In: Alessandro S, Eloisa V, Giuliano A, Gavino P (eds) Information retrieval and mining in distributed environments. Springer, Berlin, pp 1–20

    Google Scholar 

  11. Borràs J, Moreno A, Valls A (2014) Intelligent tourism recommender systems: a survey. Expert Syst Appl 41(16):7370–7389

    Article  Google Scholar 

  12. Botea A, Braghin S (2015) Contingent versus deterministic plans in multi-modal journey planning. In: Proc. of ICAPS’15, pp 268–272

  13. Botea A, Nikolova E, Berlingerio M (2013) Multi-modal journey planning in the presence of uncertainty. In: Proc. of ICAPS’13, pp 20–28

  14. Braysy O, Gendreau M (2005) Vehicle routing problem with time windows. Transp. Sci. 39(1):104–118

    Article  MATH  Google Scholar 

  15. Brilhante I, Macedo JA, Nardini FM, Perego R, Renso C (2013) Where shall we go today? Planning touristic tours with TripBuilder. In: Proc. of CIKM’13, pp 757–762

  16. Brilhante I, Macedo JA, Nardini FM, Perego R, Renso C (2014) TripBuilder: a tool for recommending sightseeing tours. In: Proc. of ECIR’14, pp 771–774

  17. Brilhante IR, Macedo JA, Nardini FM, Perego R, Renso C (2015) On planning sightseeing tours with TripBuilder. Inf Process Manag 51(2):1–15

    Article  Google Scholar 

  18. Browne CB, Powley E, Whitehouse D, Lucas SM, Cowling PI, Rohlfshagen P, Tavener S, Perez D, Samothrakis S, Colton S (2012) A survey of monte carlo tree search methods. IEEE Trans Comput Intell AI Games 4(1):1–43

    Article  Google Scholar 

  19. Burke R (2007) Hybrid web recommender systems. In: Peter B, Alfred K, Wolfgang N (eds) The adaptive web. Springer, Berlin, pp 377–408

    Chapter  Google Scholar 

  20. Cai G, Lee K, Lee I (2018) Itinerary recommender system with semantic trajectory pattern mining from geo-tagged photos. Expert Syst Appl 94:32–40

    Article  Google Scholar 

  21. Castillo L, Armengol E, Onaindía E, Sebastiá L, González-Boticario J, Rodríguez A, Fernández S, Arias JD, Borrajo D (2008) SAMAP: an user-oriented adaptive system for planning tourist visits. Expert Syst Appl 34(2):1318–1332

    Article  Google Scholar 

  22. Chekuri C, Pal M (2005) A recursive greedy algorithm for walks in directed graphs. In: Proc. of FOCS’05, pp 245–253

  23. Chen C, Chen X, Wang Z, Wang Y, Zhang D (2017) Scenicplanner: planning scenic travel routes leveraging heterogeneous user-generated digital footprints. Front Comput Sci 11(1):61–74

    Article  Google Scholar 

  24. Chen C, Zhang D, Guo B, Ma X, Pan G, Wu Z (2015) TripPlanner: personalized trip planning leveraging heterogeneous crowdsourced digital footprints. IEEE Trans Intell Transp Syst 16(3):1259–1273

    Article  Google Scholar 

  25. Chen D, Ong CS, Xie L (2016) Learning points and routes to recommend trajectories. In: Proc. of CIKM’16, pp 2227–2232

  26. Chen Y-Y, Cheng A-J, Hsu WH (2013) Travel recommendation by mining people attributes and travel group types from community-contributed photos. IEEE Trans Multimed 15(6):1283–1295

    Article  Google Scholar 

  27. Chen Z, Shen HT, Zhou X (2011) Discovering popular routes from trajectories. In: Proc. of ICDE’11, pp 900–911

  28. Cheng AJ, Chen YY, Huang YT, Hsu WH, Liao HYM (2011) Personalized travel recommendation by mining people attributes from community-contributed photos. In: Proc. of MM’11, pp 83–92

  29. Choudhury MD, Feldman M, Amer-Yahia S, Golbandi N, Lempel R, Yu C (2010) Automatic construction of travel itineraries using social breadcrumbs. In: Proc. of HT’10, pp 35–44

  30. Choudhury MD, Feldman M, Amer-Yahia S, Golbandi N, Lempel R, Yu C (2010) Constructing travel itineraries from tagged geo-temporal breadcrumbs. In: Proc. of WWW’10, pp 1083–1084

  31. Cohen R, Katzir L (2008) The generalized maximum coverage problem. Inf Process Lett 108(1):15–22

    Article  MathSciNet  MATH  Google Scholar 

  32. Conitzer V, Sandholm T (2002) Complexity of mechanism design. In: Proc. of UAI’02, pp 103–110

  33. Coulom R (2006) Efficient selectivity and backup operators in monte-carlo tree search. In: Proc. of CCG’06, pp 72–83

  34. Dorigo M, Birattari M, Stützle T (2006) Ant colony optimization. IEEE Comput Intell Mag 1(4):28–39

    Article  Google Scholar 

  35. Eppstein D (1998) Finding the k shortest paths. SIAM J Comput 28(2):652–673

    Article  MathSciNet  MATH  Google Scholar 

  36. Flórez JE, de Reyna ATA, Javier García CLL, Olaya AG, Borrajo D (2011) Planning multi-modal transportation problems. In: Proc. of ICAPS’11, pp 66–73

  37. Friggstad Z, Gollapudi S, Kollias K, Sarlos T, Swamy C, Tomkins A (2018) Orienteering algorithms for generating travel itineraries?. In: Proc. of WSDM’18, pp 180–188

  38. Fu CY, Hu MC, Lai J-H, Wang H, Wu J-L (2014) Travelbuddy: interactive travel route recommendation with a visual scene interface. In: Proc. of MMM’14, pp 219–230

  39. Galbrun E, Pelechrinis K, Terzi E (2014) Safe navigation in urban environments. In: Proc. of UrbComp’14

  40. Galbrun E, Pelechrinis K, Terzi E (2016) Urban navigation beyond shortest route: the case of safe paths. Inf Syst 57:160–171

    Article  Google Scholar 

  41. Gao H, Tang J, Liu H (2012) Exploring social-historical ties on location-based social networks. In: Proc. of ICWSM’12, pp 114–121

  42. Garcia I, Sebastia L, Onaindia E (2011) On the design of individual and group recommender systems for tourism. Expert Syst Appl 38(6):7683–7692

    Article  Google Scholar 

  43. Garcia I, Sebastia L, Onaindia E, Guzman C (2009) A group recommender system for tourist activities. In: Proc. of EC-WEB’09, pp 26–37

  44. Gavalas D, Kasapakis V, Konstantopoulos C, Pantziou G, Vathis N, Zaroliagis C (2015) The eCOMPASS multimodal tourist tour planner. Expert Syst Appl 42(21):7303–7316

    Article  Google Scholar 

  45. Gavalas D, Konstantopoulos C, Mastakas K, Pantziou G (2014) A survey on algorithmic approaches for solving tourist trip design problems. J Heuristics 20(3):291–328

    Article  Google Scholar 

  46. Gildea D, Hofmann T (1999) Topic-based language models using EM. In: Proc. of EuroSpeech’99

  47. Gionis A, Lappas T, Pelechrinis K, Terzi E (2014) Customized tour recommendations in urban areas. In: Proc. of WSDM’14, pp 313–322

  48. Gunawan A, Lau HC, Vansteenwegen P (2016) Orienteering problem: a survey of recent variants, solution approaches and applications. Eur J Oper Res 255(2):315–332

    Article  MathSciNet  MATH  Google Scholar 

  49. Han J, Pei J, Mortazavi-Asl B, Pinto H, Chen Q, Dayal U, Hsu MC (2001) Prefixspan: mining sequential patterns efficiently by prefix-projected pattern growth. In: Proc. of ICDE’01, pp 215–224

  50. Hanani U, Shapira B, Shoval P (2001) Information filtering: overview of issues, research and systems. User Model User Adapt Interact 11(3):203–259

    Article  MATH  Google Scholar 

  51. Hofmann T (1999) Probabilistic latent semantic indexing. In: Proc. of SIGIR’99, pp 50–57

  52. Hu L, Cao J, Xu G, Cao L, Gu Z, Cao W (2014) Deep modeling of group preferences for group-based recommendation. In: Proc. of AAAI’14, pp 1861–1867

  53. Jameson A, Baldes S, Kleinbauer T (2003) Enhancing mutual awareness in group recommender systems. In: Proc. of ITWP’03

  54. Jiang S, Qian X, Mei T, Fu Y (2016) Personalized travel sequence recommendation on multi-source big social media. IEEE Tran Big Data 2(1):43–56

    Article  Google Scholar 

  55. Keler A, Mazimpaka JD (2016) Safety-aware routing for motorised tourists based on open data and VGI. J Locat Based Serv 10(1):64–77

    Article  Google Scholar 

  56. Kiseleva J, Mueller MJ, Bernardi L, Davis C, Kovacek I, Einarsen MS, Kamps J, Tuzhilin A, Hiemstra D (2015) Where to go on your next trip?: optimizing travel destinations based on user preferences. In: Proc. of SIGIR’15, pp 1097–1100

  57. Kisilevich S, Mansmann F, Keim D (2010) P-dbscan: a density based clustering algorithm for exploration and analysis of attractive areas using collections of geo-tagged photos. In: Proc. of COM.Geo’10, p 38

  58. Kohavi R, Deng A, Frasca B, Walker T, Xu Y, Pohlmann N (2013) Online controlled experiments at large scale. In: Proc. of KDD’13, pp 1168–1176

  59. Kotiloglu S, Lappas T, Pelechrinis K, Repoussis P (2017) Personalized multi-period tour recommendations. Tour Manag 62:76–88

    Article  Google Scholar 

  60. Kurashima T, Iwata T, Irie G, Fujimura K (2010) Travel route recommendation using geotags in photo sharing sites. In: Proc. of CIKM’10, pp 579–588

  61. Kurashima T, Iwata T, Irie G, Fujimura K (2013) Travel route recommendation using geotagged photos. Knowl Inf Syst 37(1):37–60

    Article  Google Scholar 

  62. Leung KWT, Lee DL, Lee WC (2011) Clr: a collaborative location recommendation framework based on co-clustering. In: Proc. of SIGIR’11, pp 305–314

  63. Lewis RA, Rao JM, Reiley DH (2011) Here, there, and everywhere: correlated online behaviors can lead to overestimates of the effects of advertising. In: Proc. of WWW’11, pp 157–166

  64. Li Q, Zheng Y, Xie X, Chen Y, Liu W, Ma W-Y (2008) Mining user similarity based on location history. In: Proc. of SIGSPATIAL’08, p 34

  65. Li X, Cong G, Li X-L, Pham TAN, Krishnaswamy S (2015) Rank-geofm: a ranking based geographical factorization method for point of interest recommendation. In: Proc. of SIGIR’15, pp 433–442

  66. Lian D, Zheng VW, Xie X (2013) Collaborative filtering meets next check-in location prediction. In: Proc. of WWW’13, pp 231–232

  67. Liebig T, Piatkowski N, Bockermann C, Morik K (2014) Predictive trip planning-smart routing in smart cities. In: Proc. of MUD’14, pp 331–338

  68. Liebig T, Piatkowski N, Bockermann C, Morik K (2017) Dynamic route planning with real-time traffic predictions. Inf Syst 64:258–265

    Article  Google Scholar 

  69. Lim KH (2015) Recommending tours and places-of-interest based on user interests from geo-tagged photos. In: Proc. of SIGMOD’15 Ph.D. symposium, pp 33–38

  70. Lim KH, Chan J, Karunasekera S, Leckie C (2017) Personalized itinerary recommendation with queuing time awareness. In: Proc. of SIGIR’17, pp 325–334

  71. Lim KH, Chan J, Leckie C, Karunasekera S (2015) Personalized tour recommendation based on user interests and points of interest visit durations. In: Proc. of IJCAI’15, pp 1778–1784

  72. Lim KH, Chan J, Leckie C, Karunasekera S (2016) Towards next generation touring: personalized group tours. In: Proc. of ICAPS’16, pp 412–420

  73. Lim KH, Chan J, Leckie C, Karunasekera S (2018) Personalized trip recommendation for tourists based on user interests, points of interest visit durations and visit recency. Knowl Inf Syst 54(2):375–406

    Article  Google Scholar 

  74. Lim KH, Lim E-P, Jiang B, Achananuparp P (2016) Using online controlled experiments to examine authority effects on user behavior in email campaigns. In: Proc. of HT’16, pp 255–260

  75. Lim KH, Wang X, Chan J, Karunasekera S, Leckie C, Chen Y, Tan CL, Gao FQ, Wee TK (2016) ersTour: a personalized tour recommendation and planning system. In: Proc. of HT’16

  76. Liu Q, Wu S, Wang L, Tan T (2016) Predicting the next location: a recurrent model with spatial and temporal contexts. In: Proc. of AAAI’16, pp 194–200

  77. Lu X, Wang C, Yang J-M, Pang Y, Zhang L (2010) Photo2trip: generating travel routes from geo-tagged photos for trip planning. In: Proc. of MM’10, pp 143–152

  78. Lucchese C, Perego R, Silvestri F, Vahabi H, Venturini R (2012) How random walks can help tourism. In: Proc. of ECIR’12, pp 195–206

  79. Majid A, Chen L, Mirza HT, Hussain I, Chen G (2015) A system for mining interesting tourist locations and travel sequences from public geo-tagged photos. Data Knowl Eng 95:66–86

    Article  Google Scholar 

  80. Memon I, Chen L, Majid A, Lv M, Hussain I, Chen G (2015) Travel recommendation using geo-tagged photos in social media for tourist. Wirel Personal Commun 80(4):1347–1362

    Article  Google Scholar 

  81. Pennebaker J (2013) The secret life of pronouns: what our words say about us. Bloomsbury, London

    Google Scholar 

  82. Pham TAN, Li X, Cong G (2017) A general model for out-of-town region recommendation. In: Proc. of WWW’17, pp 401–410

  83. Quercia D, Schifanella R, Aiello LM (2014) The shortest path to happiness: recommending beautiful, quiet, and happy routes in the city. In: Proc. of HT’14, pp 116–125

  84. Refanidis I, Alexiadis A (2011) Deployment and evaluation of selfplanner, an automated individual task management system. Comput Intell 27(1):41–59

    Article  MathSciNet  Google Scholar 

  85. Refanidis I, Emmanouilidis C, Sakellariou I, Alexiadis A, Koutsiamanis R-A, Agnantis K, Tasidou A, Kokkoras F, Efraimidis PS (2014) myVisitPlanner GR: personalized itinerary planning system for tourism. In: Proc. of SETN’14, pp 615–629

  86. Refanidis I, Yorke-Smith N (2010) A constraint-based approach to scheduling an individual’s activities. ACM Trans Intell Syst Technol 1(2):12

    Article  Google Scholar 

  87. Roy SB, Lakshmanan LV, Liu R (2015) From group recommendations to group formation. In: Proc. of SIGMOD’15, pp 1603–1616

  88. Souffriau W, Vansteenwegen P (2010) Tourist trip planning functionalities: state-of-the-art and future. In: Proc. of ICWE’10, pp 474–485

  89. Souffriau W, Vansteenwegen P, Vertommen J, Berghe GV, Oudheusden DV (2008) A personalized tourist trip design algorithm for mobile tourist guides. Appl Artif Intell 22(10):964–985

    Article  Google Scholar 

  90. Spyrou E, Mylonas P (2016) A survey on Flickr multimedia research challenges. Eng Appl Artif Intell 51:71–91

    Article  Google Scholar 

  91. Su Y, Li X, Tang W, Xiang J, He Y (2018) Next check-in location prediction via footprints and friendship on location-based social networks. In: Proc. of MDM’18, pp 251–256

  92. Tang D, Agarwal A, O’Brien D, Meyer M (2010) Overlapping experiment infrastructure: more, better, faster experimentation. In: Proc. of KDD’10, pp 17–26

  93. Taylor K, Lim KH, Chan J (2018) Travel itinerary recommendations with must-see points-of-interest. In: Proc. of WWW’18, pp 1198–1205

  94. Tong H, Faloutsos C (2006) Center-piece subgraphs: problem definition and fast solutions. In: Proc. of KDD’06, pp 404–413

  95. Toyoshima M, Hirota M, Kato D, Araki T, Ishikawa H (2018) Where is the memorable travel destinations?. In: Proc. of SocInfo’18, pp 291–298

  96. Tsiligirides T (1984) Heuristic methods applied to orienteering. J Oper Res Soc 35(9):797–809

    Article  Google Scholar 

  97. UNWTO (2016) United Nations World Tourism Organization (UNWTO) annual report 2015. http://www2.unwto.org/annual-reports. Accessed 22 Oct 2017

  98. Vansteenwegen P, Oudheusden DV (2007) The mobile tourist guide: an OR opportunity. OR Insight 20(3):21–27

    Article  Google Scholar 

  99. Vansteenwegen P, Souffriau W, Berghe GV, Oudheusden DV (2009) Iterated local search for the team orienteering problem with time windows. Comput Oper Res 36(12):3281–3290

    Article  MATH  Google Scholar 

  100. Vansteenwegen P, Souffriau W, Berghe GV, Oudheusden DV (2011) The city trip planner: an expert system for tourists. Expert Syst Appl 38(6):6540–6546

    Article  Google Scholar 

  101. Vansteenwegen P, Souffriau W, Oudheusden DV (2011) The orienteering problem: a survey. Eur J Oper Res 209(1):1–10

    Article  MathSciNet  MATH  Google Scholar 

  102. Viola P, Jones M (2001) Rapid object detection using a boosted cascade of simple features. In: Proc. of CVPR’01, pp 511–518

  103. Wang J, Feng Y, Naghizade E, Rashidi L, Lim KH, Lee KE (2018) Happiness is a choice: sentiment and activity-aware location recommendation. In: Proc. of WWW’18, pp 1401–1405

  104. Wang X, Leckie C, Chan J, Lim KH, Vaithianathan T (2016) Improving personalized trip recommendation by avoiding crowds. In: Proc. of CIKM’16, pp 25–34

  105. World Travel and Tourism Council (2016) 2016 economic impact annual update summary. https://www.wttc.org/research/economic-research/economic-impact-analysis/. Accessed 22 Oct 2017

  106. Yahi A, Chassang A, Raynaud L, Duthil H, Chau DHP (2015) Aurigo: an interactive tour planner for personalized itineraries. In: Proc. of IUI’15, pp 275–285

  107. Yao L, Sheng QZ, Qin Y, Wang X, Shemshadi A, He Q (2015) Context-aware point-of-interest recommendation using tensor factorization with social regularization. In: Proc. of SIGIR’15, pp 1007–1010

  108. Ye M, Yin P, Lee W-C, Lee D-L (2011) Exploiting geographical influence for collaborative point-of-interest recommendation. In: Proc. of SIGIR’11, pp 325–334

  109. Yin P, Ye M, Lee W-C, Li Z (2014) Mining GPS data for trajectory recommendation. In: Proc. of PAKDD’14, pp 50–61

  110. Yu Z, Xu H, Yang Z, Guo B (2016) Personalized travel package with multi-point-of-interest recommendation based on crowdsourced user footprints. IEEE Trans Hum Mach Syst 46(1):151–158

    Article  Google Scholar 

  111. Yuan Q, Cong G, Lin C-Y (2014) COM: a generative model for group recommendation. In: Proc. of KDD’14, pp 163–172

  112. Yuan Q, Cong G, Ma Z, Sun A, Thalmann NM (2013) Time-aware point-of-interest recommendation. In: Proc. of SIGIR’13, pp 363–372

  113. Yuan Q, Cong G, Sun A (2014) Graph-based point-of-interest recommendation with geographical and temporal influences. In: Proc. of CIKM’14, pp 659–668

  114. Zhang C, Liang H, Wang K (2016) Trip recommendation meets real-world constraints: poi availability, diversity, and traveling time uncertainty. ACM Trans Inf Syst 35(1):5

    Google Scholar 

  115. Zhang C, Liang H, Wang K, Sun J (2015) Personalized trip recommendation with poi availability and uncertain traveling time. In: Proc. of CIKM’15, pp 911–920

  116. Zheng VW, Zheng Y, Xie X, Yang Q (2010) Collaborative location and activity recommendations with GPS history data. In: Proc. of WWW’10, pp 1029–1038

  117. Zheng Y, Xie X (2011) Learning travel recommendations from user-generated GPS traces. ACM Trans Intell Syst Technol 2(1):2

    Article  Google Scholar 

  118. Zheng Y, Zhang L, Ma Z, Xie X, Ma W-Y (2011) Recommending friends and locations based on individual location history. ACM Trans Web 5(1):5

    Article  Google Scholar 

  119. Zheng Y, Zhang L, Xie X, Ma W-Y (2009) Mining interesting locations and travel sequences from GPS trajectories. In: Proc. of WWW’09, pp 791–800

Download references

Author information

Authors and Affiliations

  1. Information Systems Technology and Design Pillar, Singapore University of Technology and Design, Singapore, Singapore

    Kwan Hui Lim

  2. School of Computing and Information Systems, The University of Melbourne, Parkville, Australia

    Jeffrey Chan, Shanika Karunasekera & Christopher Leckie

  3. School of Science, RMIT University, Melbourne, Australia

    Jeffrey Chan

Authors
  1. Kwan Hui Lim
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jeffrey Chan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Shanika Karunasekera
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Christopher Leckie
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kwan Hui Lim.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lim, K.H., Chan, J., Karunasekera, S. et al. Tour recommendation and trip planning using location-based social media: a survey. Knowl Inf Syst 60, 1247–1275 (2019). https://doi.org/10.1007/s10115-018-1297-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10115-018-1297-4

Keywords

Search

Navigation