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MultiCity: A Personalized Multi-itinerary City Recommendation Engine

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).

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