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• W2784296973 abstract "Tourism and Travel sector are improving services through the use of a large amount of data gathered from different sources. The ease access to reviews, rating and experiences from different tourists made the touristic planning rich and complex. Hence, a big challenge faced by tourism sector is to use the gathered data for detecting tourist preferences. In this work, we proposed a solution able to detecting tourist implicit preferences based on photos. We used emerging techniques such as Convolutional Neural Network and fuzzy logic to classify tourists in five categories. Finally, a set of photos were analyzed and the results reached over 82% on accuracy metric for all classifiers." @default.
• W2784296973 created "2018-01-26" @default.
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• W2784296973 date "2017-12-01" @default.
• W2784296973 modified "2023-10-02" @default.
• W2784296973 title "Using social media photos to identify tourism preferences in smart tourism destination" @default.
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• W2784296973 doi "https://doi.org/10.1109/bigdata.2017.8258423" @default.
• W2784296973 hasPublicationYear "2017" @default.
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