Travel Recommendation System Using Content and Collaborative Filtering

Shaurya Goel; Prof. (Dr) S.W.A. Rizvi

doi:10.54060/a2zjournals.jmce.63

Authors

Shaurya Goel Department of Computer Science & Engineering, Amity School of Engineering & Technology Lucknow, Amity University Uttar Pradesh, India
Prof. (Dr) S.W.A. Rizvi Department of Computer Science & Engineering, Amity School of Engineering & Technology Lucknow, Amity University Uttar Pradesh, India

DOI:

https://doi.org/10.54060/a2zjournals.jmce.63

Keywords:

Collaborative Filtering, Content Filtering, Information Filters

Abstract

Tourism significantly impacts a nation's economy, yet there remains a void in platforms offering tailored information on local attractions. In our study, we propose a hybrid recommendation system amalgamating content and collaborative filtering methods to provide personalized tourist suggestions. This approach mitigates individual methods' drawbacks, enhancing recommendations' accuracy. To gauge item similarity, we employ cosine similarity while integrating SVD within a model-based collaborative filtering framework for improved outcomes. By utilizing a weighted hybridization technique, we effectively merge the outputs of both approaches. We collected tourist attraction and user data for implementation, yielding superior results compared to standalone content-based and collaborative filtering methods.

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References

V. Garipelly; P. T. Adusumalli; P. Singh, “12th International Conference on Computing Communication and Networking Technologies (ICCCNT)”, IEEE,06-08 July 2021.

A. Rula, A. S. Hamid, and J. K. Albahri, “How smart is e-tourism? A systematic review of smart tourism recommendation system applying data management,” vol. 39, no. 2021, pp. 100337, 2021.

P. Yochum, L. Chang, T. Gu, and M. Zhu, “Linked open data in location-based recommendation system on tourism do-main: A survey,” IEEE Access, vol. 8, pp. 16409–16439, 2020.

Z. A. Moud and H. V. Nejad, “Tourism recommendation system based on semantic clustering and sentiment analysis”, vol. 167, no. 2021, pp. 114324. 2021.

C.-S. Jeong, K.-H. Ryu, and J.-Y. Lee, “Deep Learning-based Tourism Recommendation System using Social Network Analy-sis,” International Journal of Internet Broadcasting and Communication, vol. 12, no. 2, pp. 113–119, 2020.

M. Wang, “Applying Internet information technology combined with deep learning to tourism collaborative recommen-dation system,” PLoS One, vol. 15, no. 12, p. e0240656, 2020.

Shini and A. Sreekumar, "An extensive study on the evolution of context-aware personalized travel recommender sys-tems", Information Processing Management, vol. 57, no. 1, pp. 102078, 2020.

C. T. Gu, Y. Sun and L. Chang, “A Travel Route Recommendation System Based on Smart Phones and IoT Environ-ment,” Wireless Communications and Mobile Computing, vol. 2019, 2019.

Z. Pu, H. Du, S. Yu, and D. Feng, “Improved tourism recommendation system,” in Proceedings of the 2020 12th Internation-al Conference on Machine Learning and Computing, pp. 121-126, 2020.

M. Dhaware and P. Vanwari, “A tourism and travel recommendation system based on user-location vector,” in Lecture Notes in Electrical Engineering, Singapore: Springer Singapore, 2020, pp. 1429–1437.

J. Akilandeswari, G. Jothi, K. Dhanasekaran, K. Kousalya, and V. Sathiyamoorthi, “Hybrid fire-fly-ontology-based clustering algorithm for analyzing tweets to extract causal factors,” Int. J. Semant. Web Inf. Syst. (IJSWIS), vol. 18, no. 1, pp. 1–27, 2022.

P. Ni Wayan, “Literature Review Recommendation System Using Hybrid Method by Utilizing Social Media as Market-ing,” Computer Engineering and Applications Journal, vol. 10, no. 2, pp. 105–113, 2021.

E. Omrani, B. Khoshnevisan, S. Shamshirband, H. Saboohi, N. B. Anuar, and M. H. N. Nasir, “Potential of radial basis func-tion based support vector regression for apple unwellness detection,” J. Measuring, pp. 233–252, 2014.

W. Yin, Y. Sun, and J. Zhao, “Personalized tourism route recommendation system based on dynamic clustering of user groups,” in 2021 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC), 2021.

K. A. Fararni, F. Nafis, B. Aghoutane, A. Yahyaouy, J. Riffi, and A. Sabri, “Hybrid recommender system for tourism based on big data and AI: A conceptual framework,” Big Data Min. Anal., vol. 4, no. 1, pp. 47–55, 2021.