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Multi criteria based personalized recommendation service using analytical hierarchy process for airbnb

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Abstract

There are many accommodation rental services like Hotels.com, Hotels Combined, Trivago, Airbnb, and so on. Airbnb, in particular, uses the service known as P2P (peer to peer) technology. When the guest searches for rooms or a house to rent, he or she will have to consider a lot of information that Airbnb provides to the guest such as photos of the room/house, the host, rating of reviews, number of reviews, number of guests who can stay, number of bedrooms and bathrooms, description of the room, price. When there is a lot of information, it needs to be displayed effectively. Otherwise, it can complicate the guest’s choice. This research aims to make a personalized recommendation model and to analyze the guest preferences for accommodation using Airbnb. For this process, the study constructs criteria from accommodation information in Airbnb and it calculates and analyzes the guest’s preference by AHP (Analytic Hierarchy Process). The result shows the optimal room choices from the Airbnb website according to the guest’s preferences.

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Authors and Affiliations

  1. Humanitas College, Kyung Hee University, 1 Hoegi-dong, Dongdaemun-gu, Seoul, 130-701, Republic of Korea

    Hwa-Young Jeong

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Correspondence to Hwa-Young Jeong.

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Jeong, HY. Multi criteria based personalized recommendation service using analytical hierarchy process for airbnb. J Supercomput 77, 13224–13242 (2021). https://doi.org/10.1007/s11227-021-03812-6

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  • DOI: https://doi.org/10.1007/s11227-021-03812-6

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