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gTour: Multiple itinerary recommendation engine for group of tourists

Publication Type : Journal Article

Source : Expert Systems With Applications, 2022

Url : https://www.sciencedirect.com/science/article/pii/S0957417421015086

Campus : Amaravati

School : School of Computing

Department : Computer Science

Verified : No

Year : 2022

Abstract : Tourism is currently extremely significant in the world because it is one of a country’s primary sources of revenue and employment. Tourists experience a number of challenges in selecting suitable trips, consisting of a range of itineraries in relation to their interest preferences and distinct limitations. Tourists may also want to visit in a group, e.g. members of the families or friends. In such scenario it is very difficult to please each and every member of the group individually. In this article, we propose an algorithm named as to solve these problems. The gTour algorithm is designed specifically to suggest multiple itineraries for a group. The gTour algorithm also works if a tourist decides to explore unknown places where the tourists have no past travel history. The performance of the proposed technique has been analyzed using Flickr dataset. The performance comparison shows that the proposed gTour algorithm performs better than other baseline algorithms.

Cite this Research Publication : Sarkar, J L., Majumder, A. (2022). gTour: Multiple Itinerary Recommendation Engine for Group of Tourists, Expert Systems With Applications, 191, 116190 , IF:8.665, Elsevier.

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