The evolution of travel recommender systems: A comprehensive review

Downloads

DOI:

https://doi.org/10.26637/MJM0804/0075

Abstract

Travel has always been innate desire of human beings. People wanted to travel irrespective of any hurdles like geographical barrier, age, gender, or colour with different motivations. Nowadays travel and adventure
became the most trending entertainment as well. Planning a trip is a time-consuming and herculean task for inexperienced travelers. Here comes the possibility of expert opinion for scheduling a perfect travel plan. With the development of information technology and social media, there are numerous possibilities and opportunities in fetching suitable information which can turn out to set up an appropriate travel plan and hence enhance the quality of travel. The significance of a Recommender System (RS) comes in the picture which can address travel-related queries. Personalized Travel RS will add more customization and user-specific features than Automatic Travel RS. In this paper, we conducted a detailed review and chronological evolutions of various methods and techniques used in the travel and tourism sector and compared their efficiency in Recommendations.

Keywords:

Artificial Intelligence, Recommender Systems, Autoencoders,, PTRS,, Travel and Tourism

Mathematics Subject Classification:

Mathematics
  • Pages: 1777-1785
  • Date Published: 01-01-2020
  • Vol. 8 No. 04 (2020): Malaya Journal of Matematik (MJM)

Ana reyes-menendez, Jose ramonsaura and Juan gabrielmartinez-navalon, The Impact of e-WOM on Hotels Management Reputation: Exploring Trip Advisor Review Credibility With the ELM Model, IEEE, Digital Object Identifier, (2019), 2169-3536.

C. A. Gomez-Uribe and N. Hunt, The netflixrecom-mender system: Algorithms, business value, and innovation, TMIS, 2016.

J. Delgado and R. Davidson, Knowledge Bases and User Profiling in Hospitality and Travel Recommender Systems, Procs. of the ENTER Conference, (2002), 1-16.

Jingjing Hu, Linzhu Liu, Changyou Zhang, Jialing He, Changzhen Hu, Hybrid Recommendation Algorithm Based on Latent Factor Model and Personal Rank, Journal of Internet Technology, 19(3), (2018).

ShiniRenjith, A. Sreekumara and M. Jathavedana, An extensive study on the evolution of contextaware personalized travel recommender systems, https://doi.org/10.1016/j.ipm.2019.102078, (2019).

Poonam B. Thorat, R.M. Goudar, Sunita Barve, Survey on Collaborative Filtering, Content-based Filtering and Hybrid Recommendation System, International Journal of Computer Applications, 110(4), (2015).

S.M. Mahdi Seyednezhad, Kailey Nobuko Cozart, et.al, A Review on Recommendation Systems: Context-aware to Social-based, arXiv:1811.11866v1 [cs.IR], 2018.

Guibing Guo, J. Masthoff, Resolving Data Sparsity and Cold Start in Recommender Systems, Springer-Verlag Berlin Heidelberg, 2012.

] Gilbert Badaro, Hazem Hajj, Wassim El-Hajj, Lama Nachman, A Hybrid Approach with Collaborative Filtering for Recommender Systems, IEEE, 2013.

Vipul Vekariya, G.R. Kulkarni, Hybrid Recommender systems: survey and experiments, Proceedings of the 2012 Digital Information and Communication Technology and it's Applications (DICTAP), (2012), 469-473.

Farhin Mansur, Vibha Patel, Mihir Patel, A Review on Recommender Systems, International Conference on Innovations in information Embedded and Communication Systems (ICIIECS), 2017.

Kinjal Chaudhari1, Ankit Thakkar, A Comprehensive Survey on Travel Recommender Systems, Archives of Computational Methods in Engineering, 2019. https://doi.org/10.1007/s11831-019-09363-7.

D. Gavalas, V. Kasapakis, C. Konstantopoulos, K. Mastakas and G. Pantziou, A survey on mobile tourism recommender systems, In: 2013 third international conference on communications and information technology (ICCIT), (2013), 131-135.

F. Xia, N. Y. Asabere, A. M. Ahmed, J. Li and X. Kong, Mobile multimedia recommendation in smart communities: a survey, IEEE Access 1(606), (2013).

D. Gavalas, C. Konstantopoulos, K. Mastakas and G. Pantziou, Mobile recommender systems in tourism, $J$ NetwComputAppl, 39(319), (2013).

J. Borràs, A. Moreno, A. Valls, Intelligent tourism recommender systems: a survey, Expert SystAppl, 41(16), (2014).

C. Anderson, A survey of food recommenders, arXiv preprint arXiv :1809.02862, 2018.

J. Lu, D. Wu, M. Mao, W. Wang and G. Zhang, Recommender system application developments: a survey, Decis Support Syst, 74(12), (2015).

A. Felfernig, S. Gordea, D. Jannach, E. Teppan and M. Zanker, A short survey of recommendation technologies in travel and tourism, OEGAI J, 25(7), (2007).

Shah Khusro, Zafar Ali and Irfan Ullah, Recommender Systems: Issues, Challenges and Research Opportunities, Springer Science+Business Media Singapore, 2016 .

M. Nilashi, O. bin Ibrahim, N. Ithnin, N. H. Sarmin, A multi-criteria collaborative filtering recommender system for the tourism domain using expectation maximization (EM) and PCA-ANFIS, Electron Commer Res Appl 14(6), (2015).

Zulkefli NABM, B. B. Baharudin, Hotel travel recommendation based on blog information, In: International symposium on mathematical sciences and computing research (iSMSC). IEEE, (2015), 243-248.

C. Paola, L. Serguei and C. Carlos, Tourist Information Evaluation Using a Social Network, J. of Advances in Computer Networks, 2(2014).

Z. Zhang, Y. Morimoto, Collaborative hotel recommendation based on topic and sentiment of review comments, In: proceeding of the 9 th forum for information and engineering, DEIM Forum, 2017.

J. Jonghyun Han, B. Hyunju Lee, Adaptive landmark recommendations for travel planning: Personalizing and clustering landmarks using geo-tagged social media, Journal of Pervasive and Mobile Computing, 18(2015), 4-17.

] P Sushmita Singh, A Review on Travel Recommendation Techniques, International Journal of Scientific and Engineering Research, 9(10), (2018).

H. Kori, S. Hattori, T. Tezuka and K. Tanaka, Automatic Generation of Multimedia Tour Guide from local blogs, In Proceedings of 13th International Conference on Multimedia Modeling, LNCS 4351, Part I, Springer-Verlag Berlin Heidelberg, 2007.

E. H. C. Lu, C. Y. Lin and V. S. Tseng, Trip-Mine: An Efficient Trip Planning Approach with Travel Time Constraints, 12th IEEE International Conference on Mobile Data Management, 2011.

W.G.R.M.P.S. Rathnayake, Google Maps Based Travel Planning and Analyzing System (TPAS), IEEE, Proceeding of 2018 IEEE International Conference on Current Trends toward Converging Technologies, Coimbatore, India, 2018.

S. Shelar, P. Kamat, A. Varpe and A. Birajdar, TRAVELMATE travel package recommendation system, International Research Journal of Engineering and Technology (IRJET), 5(3), (2018).

Jia-Ching Ying, Eric Hsueh-Chan Lu, Chi-Min Huang, Kuan-Cheng Kuo, Yu-Hsien Hsiao and Vincent S. Tseng, A Framework for Cloud-based POI Search and Trip Planning Systems, IEEE Transactions, 2013.

Wafa Shafqat and Yung-Cheol Byun, A Recommendation Mechanism for Under-Emphasized Tourist Spots Using Topic Modeling and Sentiment Analysis, Sustainability, 31(2019).

RizwanaKallooraviThandil, K.P Muhamed Basheer, Rababa Kareem Kollathodi, Automatic speech recognition system for utterances in Malayalam language, Malaya Journal of Matematik, S(1), (2019), 560-565.

C. Valliyammai, R. PrasannaVenkatesh, C. Vennila, S. Gopi Krishnan, An Intelligent Personalized Recommendation for Travel Group Planning based on Reviews, (2016) IEEE Eighth International Conference on Advanced Computing (ICoAC), 2016.

H. Wang, N. Wang, and D. Y. Yeung, Collaborative deep learning for recommender systems, KDD'15, Sydney, NSW, Australia, 2015.

P. Vincent, H. Larochelle, I. Lajoie, Y. Bengio, and P. A. Manzagol, Stacked denoising autoencoders:Learning useful representations in a deep network with a local denoising criterion, $J M L R, 11(2010)$.

S. Sedhain, A. K. Menon, S. Sanner, and L. Xie, Autorec:Autoencoders meet collaborative filtering, 2015. http://dx.doi.org/10.1145/2740908.2742726.

Qibing Li, Xiaolin Zheng, Xinyue Wu, Neural Collaborative Autoencoder, IEEE Transactions on Knowledge and Data Engineering, arXiv:1712.09043v3[cs.LG], 2018.

D. Ajantha, Jobi Vijay, Raji Sridhar, A userlocation vector based approach for personalised tourism and travel rec-ommendation, International Conference on Big Data Analytics and Computational Intelligence (ICBDAC), 2017.

Eric Hsueh-Chan Lu, Ching-Yu Chen, Vincent S. Tseng, Personalized trip recommendation with multiple constraints by mining user check-in behaviors, Proceedings of the 20th International Conference on Advances in Geographic Information Systems, 2012.

  • NA

Metrics

Metrics Loading ...

Published

01-01-2020

How to Cite

V. K. Muneer, and K. P. Mohamed Basheer. “The Evolution of Travel Recommender Systems: A Comprehensive Review”. Malaya Journal of Matematik, vol. 8, no. 04, Jan. 2020, pp. 1777-85, doi:10.26637/MJM0804/0075.