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Publication Type : Conference Proceedings
Source : International Conference on Computational Intelligence and Data Analytics (ICCIDA), 2022
Url : https://link.springer.com/chapter/10.1007/978-981-19-3391-2_39
Campus : Amaravati
School : School of Computing
Verified : No
Year : 2022
Abstract : Tourism plays a vital role for every nation today, as it can generate a large number of jobs and is the major source of revenue. Tourists face a lot of difficulties in choosing their itineraries in terms of their interest, popularity and a number of constraints. In general, it is also hard to suggest a certain city to a traveler. This work is useful for tourists who desire to visit various cities across the world. The proposed approach MultiCity recommends multiple cities keeping in mind interest, popularity and travel costs. The proposed MultiCity approach results reveals that it outperforms benchmark approaches with respect to real-life values.
Cite this Research Publication : Sarkar, J L., Majumder, A. MultiCity: A Personalized Multi-Itinerary City Recommendation Engine, International Conference on Computational Intelligence and Data Analytics (ICCIDA) (Accepted).