Hotel recommendation approach based on the online consumer reviews using interval neutrosophic linguistic numbers

With the popularity of online hotels booking, increasing attention has been paid to hotel recommendation methods. To provide personalized hotel recommendation for different types of consumers, a new hotel recommendation approach is proposed based on consumers' online reviews using interval neutrosophic linguistic numbers (INLNs). Meanwhile, this paper puts forward a distance formula of the interval neutrosophic linguistic numbers and the interval neutrosophic linguistic numbers power average (INLNPA) operator, making a further extension on the basis of the INLNs. Moreover, we develop a novel integration model utilizing the INLNPA operator that takes into consideration the relevance of the similar groups. And we apply the proposed approach to the hotel recommendation. In the case study, we have extracted 1902 online reviews of 10 hotels from TripAdvisor.com to verify the reliability of the proposed approach. The main conclusion of this paper is that the reliability of the hotel ordering can be improved by using the proposed approach.