Abstract
Crowdsourcing has become an essential source of information for tourists and tourism industry. Every day, large volumes of data are exchanged among stakeholders in the form of searches, posts, shares, reviews or ratings. Specifically, this paper explores inter-guest trust and similarity post-filtering, using crowdsourced ratings collected from the Expedia and TripAdvisor platforms, to improve hotel recommendations generated by incremental collaborative filtering. First, the profiles of hotels and guests are created using multi-criteria ratings and inter-guest trust and similarity. Next, incremental model-based collaborative filtering is adopted to predict unknown hotel ratings based on the multi-criteria ratings and, finally, post-recommendation filtering sorts the generated predictions based on the inter-guest trust and similarity. The proposed method was tested both off-line (post-processing) and on-line (real time processing) for performance comparison. The results highlight: (i) the increase of the quality of recommendations with the inter-guest trust and similarity; and (ii) the decrease of the predictive errors with the on-line incremental collaborative filtering. Thus, this work contributes with a novel method, integrating incremental collaborative filtering and inter-guest trust and similarity post-filtering, for on-line hotel recommendation based on multi-criteria crowdsourced rating streams.
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Acknowledgements
This paper is based upon work from COST Action IC1406 High-Performance Modelling and Simulation for Big Data Applications (cHiPSet), supported by COST (European Cooperation in Science and Technology). This work was partially supported by the European Regional Development Fund (ERDF) through (i) the Operational Programme for Competitiveness and Internationalisation - COMPETE Programme - within project «FCOMP-01-0202-FEDER-023151» and project «POCI-01-0145-FEDER-006961», and by National Funds through Fundaão para a Ciência e a Tecnologia (FCT) - Portuguese Foundation for Science and Technology - as part of project UID/EEA/50014/2013; and (ii) the Galician Regional Government under agreement for funding the Atlantic Research Center for Information and Communication Technologies (atlanTTic).
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Leal, F., Malheiro, B., Burguillo, J.C. (2019). Incremental Hotel Recommendation with Inter-guest Trust and Similarity Post-filtering. In: Rocha, Á., Adeli, H., Reis, L., Costanzo, S. (eds) New Knowledge in Information Systems and Technologies. WorldCIST'19 2019. Advances in Intelligent Systems and Computing, vol 930. Springer, Cham. https://doi.org/10.1007/978-3-030-16181-1_25
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