Airbnb Host Recommendation Engine

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Date

2021

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MEF Üniversitesi Fen Bilimleri Enstitüsü

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Abstract

In this project, a fifth rule is proposed to reveal guests ' comments about hosts using the recommendation system and sentiment analysis for the super hosts' selection for Airbnb. This project is aimed to contribute to Airbnb's selection of Super hosts. In this study, sentiment analysis and comment data are examined, and polarity scores are created for use in suggestion systems. A collaborative filtering method is used for the recommendation system. The FunkSVD algorithm received the best RMSE score. Polarity scores are estimated for each latent user by looking at the host and listing id. The recommendation system developed ranked the polarity scores of hosts for each user.

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Öneri Sistemleri, İşbirlikçi Öneri Sistemleri, Duygu Analizi

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Citation

Arslan, B. (2021). AirBnb Host Recommendation Engine. MEF Üniversitesi Fen Bilimleri Enstitüsü, Büyük Veri Analitiği Yüksek Lisans Programı. ss. 1-21

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1-21

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256

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394

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