Please use this identifier to cite or link to this item: http://hdl.handle.net/11328/4051
Title: A 2020 perspective on “Online guest profiling and hotel recommendation”: Reliability, scalability, traceability and transparency
Authors: Veloso, Bruno
Leal, Fátima
Malheiro, Benedita
Burguillo, Juan Carlos
Keywords: Data stream mining
Profiling
Recommendation
Post-filtering
Issue Date: Apr-2020
Citation: Veloso, B., Leal, F., Malheiro, B., & Burguillo, J. C. (2020). A 2020 perspective on “Online guest profiling and hotel recommendation”: Reliability, scalability, traceability and transparency. Electronic Commerce Research and Applications, 40(March–April 2020), 100957. https://doi.org/10.1016/j.elerap.2020.100957. Repositório Institucional UPT. http://hdl.handle.net/11328/4051
Abstract: Tourism crowdsourcing platforms accumulate and use large volumes of feedback data on tourism-related services to provide personalized recommendations with high impact on future tourist behavior. Typically, these recommendation engines build individual tourist profiles and suggest hotels, restaurants, attractions or routes based on the shared ratings, reviews, photos, videos or likes. Due to the dynamic nature of this scenario, where the crowd produces a continuous stream of events, we have been exploring stream-based recommendation methods, using stochastic gradient descent (SGD), to incrementally update the prediction models and post-filters to reduce the search space and improve the recommendation accuracy. In this context, we offer an update and comment on our previous article (Veloso et al., 2019a) by providing a recent literature review and identifying the challenges laying ahead concerning the online recommendation of tourism resources supported by crowdsourced data.
URI: http://hdl.handle.net/11328/4051
ISSN: 1567-4223 (Print)
Appears in Collections:REMIT – Artigos em Revistas Internacionais / Papers in International Journals

Files in This Item:
File Description SizeFormat 
A 2020 perspective on Online guest profiling.pdf126.35 kBAdobe PDFView/Open    Request a copy


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.