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- W2904550117 abstract "For tourist attraction recommendation, there are three essential aspects to be considered: tourist preferences, attraction themes, and sentiments on themes of attraction. By utilizing vast multi-modal media available on Internet, this paper is aiming to develop an efficient solution of tourist attraction recommendation covering all these three aspects. To achieve this goal, we propose a probabilistic generative model called Sentiment-aware Multi-modal Topic Model (SMTM), whose advantages are four folds: (1) we separate tourists and attractions into two domains for better recovering tourist topics and attraction themes; (2) we investigate tourists sentiments on topics to retain the preference ones; (3) the recommended attraction is guaranteed with positive sentiment on the related attraction themes; (4) the multi-modal data are utilized to enhance the recommendation accuracy. Qualitative and quantitative evaluation results have validated the effectiveness of our method." @default.
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- W2904550117 date "2018-12-08" @default.
- W2904550117 modified "2023-09-28" @default.
- W2904550117 title "Sentiment-Aware Multi-modal Recommendation on Tourist Attractions" @default.
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- W2904550117 doi "https://doi.org/10.1007/978-3-030-05710-7_1" @default.
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