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dc.contributor.advisorÖzgür Özlüken_US
dc.contributor.authorArslan, Batuhan
dc.date.accessioned2021-12-14T11:21:13Z
dc.date.available2021-12-14T11:21:13Z
dc.date.issued2021en_US
dc.identifier.citationArslan, B. (2021). AirBnb Host Recommendation Engine. MEF Üniversitesi Fen Bilimleri Enstitüsü, Büyük Veri Analitiği Yüksek Lisans Programı. ss. 1-21en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11779/1694
dc.description.abstractIn 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.en_US
dc.language.isoengen_US
dc.publisherMEF Üniversitesi Fen Bilimleri Enstitüsüen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectÖneri Sistemleri, İşbirlikçi Öneri Sistemleri, Duygu Analizien_US
dc.titleAirBnb host recommendation engineen_US
dc.title.alternativeAirBnb ev sahibi öneri sistemien_US
dc.typeYL-Bitirme Projesien_US
dc.departmentBüyük Veri Analitiği Yüksek Lisans Programıen_US
dc.identifier.startpage1-21en_US
dc.relation.publicationcategoryYL-Bitirme Projesien_US
dc.contributor.institutionauthorArslan, Batuhan


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