Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.11779/1694
Title: | Airbnb Host Recommendation Engine | Other Titles: | AirBnb ev sahibi öneri sistemi | Authors: | Arslan, Batuhan | Advisors: | Özgür Özlük | Keywords: | Öneri Sistemleri, İşbirlikçi Öneri Sistemleri, Duygu Analizi | Publisher: | MEF Üniversitesi Fen Bilimleri Enstitüsü | Source: | Arslan, B. (2021). AirBnb Host Recommendation Engine. MEF Üniversitesi Fen Bilimleri Enstitüsü, Büyük Veri Analitiği Yüksek Lisans Programı. ss. 1-21 | 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. | URI: | https://hdl.handle.net/20.500.11779/1694 |
Appears in Collections: | FBE, Yüksek Lisans, Proje Koleksiyonu |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
FBE_BüyükVeriAnalitiği_BatuhanArslan.pdf | YL-Proje Dosyası | 858.43 kB | Adobe PDF | View/Open |
CORE Recommender
Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.