Recommender Systems is one of the most useful application of machine learning. They are collection of simple algorithms which tend to provide most relevant and accurate data as per user’s requirement. Travel and Tourism domain is one of the important economic area of a nation and recommender systems in this domain would cater to not only the tourists but also to the governments. This paper is a study of the various recommender systems available in the field of travel and tourism.

Point of Interst(POI), Collaborative filtering, Hybrid Filtering, Recommender System, weather condition

[1] V. Subramaniyaswamy, V. Vijayakumar, R. Logesh and V. Indragandhi, "Intelligent Travel Recommendation System by Mining Attributes from Community Contributed Photos", Procedia Computer Science, vol. 50, pp. 447-455, 2015. Available: 10.1016/j.procs.2015.04.014.
[2] C. Aggarwal, Recommender Systems. Cham: Springer International Publishing, 2016.
[3] R. Iateilang and C. L, "Recommender Systems: Types of Filtering Techniques", International Journal of Engineering Research & Technology (IJERT), vol. 3, no. 11, pp. 251 - 253, 2014.
[4] K. Nagwekar and P. Shirsat, "A Community Detection and Recommendation System", IJARCCE, vol. 6, no. 1, pp. 7-13, 2017. Available: 10.17148/ijarcce.2017.6102.
[5] G. A. Sielis, A. Tzanavari, and G. A. Papadopoulos, “Recommender Systems Review of Types, Techniques, and Applications,” Encyclopedia of Information Science and Technology, Third Edition, pp. 7260–7270
[6] Q. Liu, E. Chen, H. Xiong, Y. Ge, Z. Li, and X. Wu, “A Cocktail Approach for Travel Package Recommendation,” IEEE Transactions on Knowledge and Data Engineering, vol. 26, no. 2, pp. 278–293, 2014.
[7] L. T. Yong, “A collaborative awareness framework for mobile tourist recommender system,” 2011 3rd International Conference on Computer Research and Development, 2011.
[8] E. Ashley-Dejo, S. Ngwira, and T. Zuva, “A context-aware proactive recommender system for tourist,” 2016 International Conference on Advances in Computing and Communication Engineering (ICACCE), 2016.
[9] K. Kesorn, W. Juraphanthong, and A. Salaiwarakul, “Personalized Attraction Recommendation System for Tourists Through Check-In Data,” IEEE Access, vol. 5, pp. 26703–26721, 2017.
[10] N. Wijaya and A. Furqan, “Coastal Tourism and Climate-Related Disasters in an Archipelago Country of Indonesia: Tourists’ Perspective,” Procedia Engineering, vol. 212, pp. 535–542, 2018.
[11] A. Umanets, A. Ferreira, and N. Leite, “GuideMe – A Tourist Guide with a Recommender System and Social Interaction,” Procedia Technology, vol. 17, pp. 407–414, 2014.
[12] M. Thenmozhi, S. Harshitha, M. Gayathidevi, and C. S. Reddy, “A framework for tourist recommendation system exploiting geo-tagged photos,” 2016 10th International Conference on Intelligent Systems and Control (ISCO), 2016.
[13] Titan, L. S. Sanjaya, and Ferdianto, “Influential factors on travel decision in e-tourism,” 2016 International Conference on Information Management and Technology (ICIMTech), 2016.
[14] M. Sumardi, Jufery, Frenky, R. Wongso, and F. A. Luwinda, “‘TripBuddy’ Travel Planner with Recommendation based on User‘s Browsing Behaviour,” Procedia Computer Science, vol. 116, pp. 326–333, 2017.
[15] L. Ravi and S. Vairavasundaram, “A Collaborative Location Based Travel Recommendation System through Enhanced Rating Prediction for the Group of Users,” Computational Intelligence and Neuroscience, vol. 2016, pp. 1–28, 2016.
[16] M. E. B. H. Kbaier, H. Masri, and S. Krichen, “A Personalized Hybrid Tourism Recommender System,” 2017 IEEE/ACS 14th International Conference on Computer Systems and Applications (AICCSA), 2017.
[17] J. D. C. L. Soares, Suyoto, and A. J. Santoso, “M-Guide: Hybrid Recommender System Tourism In East-Timor,” 2017 International Conference on Soft Computing, Intelligent System and Information Technology (ICSIIT), 2017.
[18] C.-S. Wang, C.-C. Yeh, and C.-Y. Li, “Intelligence traveling schedule recommender based on commonsense reasoning algorithm,” International Conference on Computer and Communication Engineering (ICCCE10), 2010.
[19] G.-S. Fang, S. Kamei, and S. Fujita, “Automatic Generation of Temporal Feature Vectors with Application to Tourism Recommender Systems,” 2016 Fourth International Symposium on Computing and Networking (CANDAR), 2016.
[20] A. Kumar, S. Gupta, S. K. Singh, and K. K. Shukla, “Comparison of various metrics used in collaborative filtering for recommendation system,” 2015 Eighth International Conference on Contemporary Computing (IC3), 2015.
[21] H. Hu and X. Zhou, “Recommendation of Tourist Attractions Based on Slope One Algorithm,” 2017 9th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2017.
[22] T. Izumi, T. Kitamura, and Y. Nakatani, “A Suggestive Recommendation Method to Make Tourists ‘Feel like going,’” IFAC-PapersOnLine, vol. 49, no. 19, pp. 573–578, 2016.
[23] I. Y. Choi, J. K. Kim, and Y. U. Ryu, “A Two-Tiered Recommender System for Tourism Product Recommendations,” 2015 48th Hawaii International Conference on System Sciences, 2015.
[24] L. Etaati and D. Sundaram, “Adaptive tourist recommendation system: conceptual frameworks and implementations,” Vietnam Journal of Computer Science, vol. 2, no. 2, pp. 95–107, 2014.
[25] G. Hirakawa, G. Satoh, K. Hisazumi, and Y. Shibata, “Data Gathering System for Recommender System in Tourism,” 2015 18th International Conference on Network-Based Information Systems, 2015.
[26] K. A. Achmad, L. E. Nugroho, Widyawan, and A. Djunaedi, “Linking multidimensional context to support tourism recommender system,” 2017 3rd International Conference on Science and Technology - Computer (ICST), 2017.
[27] K. A. Achmad, L. E. Nugroho, Widyawan, and A. Djunaedi, “Tourism contextual information for recommender system,” 2017 7th International Annual Engineering Seminar (InAES), 2017.
[28] Z. Xu, “Trip similarity computation for context-aware travel recommendation exploiting geotagged photos,” 2014 IEEE 30th International Conference on Data Engineering Workshops, 2014.
[29] S.-P. Lin, C.-L. Yang, H.-C. Pi, and T.-M. Ho, “Tourism guide cloud service quality: What actually delights customers?,” SpringerPlus, vol. 5, no. 1, 2016.
[30] J. Borràs, A. Moreno, and A. Valls, “Intelligent tourism recommender systems: A survey,” Expert Systems with Applications, vol. 41, no. 16, pp. 7370–7389, 2014.
[31] C. Chantrapornchai and C. Choksuchat, “Ontology construction and application in practice case study of health tourism in Thailand,” SpringerPlus, vol. 5, no. 1, 2016.
[32] C.-I. Lee, T.-C. Hsia, H.-C. Hsu, and J.-Y. Lin, “Ontology-based tourism recommendation system,” 2017 4th International Conference on Industrial Engineering and Applications (ICIEA), 2017.
[33] C. Zhang, “The design of Scenic tourist service system,” Procedia Computer Science, vol. 131, pp. 1253–1259, 2018.
[34] Patel, M. and Barot, P, “Optimization of Cold Start Problem in Recommendation Systems : A Review” International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), vol. 5, no. 7, 2019.
[35] Bheema Shireesha, Navuluri Madhavilatha, and Chunduru Anilkumar, “Movie Recommended System by Using Collaborative Filtering” International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), vol. 5, no. 1, 2019.
[36] N. Rajganesh, C. Asha, A. T. Keerthana, and K. Suriya, “A Hybrid Feedback Based Book Recommendation System Using Sentiment Analysis” International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), vol. 3, no. 3, 2018.