Abstract
The success of a social photo recommendation system mainly depends on its ability to provide high quality photos, which also means the recommended photos will have a greater chance to meet the interests of the users. We believe the quality of photos may originate from three dimensions. Two experiments was conducted to validate the relation of various features from these dimensions and the attractiveness of social photos. Result show, by integrated use of three dimensions, classifiers could be constructed effectively with fewer features.
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Wu, Z., Gu, Z., Dong, Z. (2013). Multi-dimensional Aesthetics Mining for Social Photo Recommendation. In: Stephanidis, C. (eds) HCI International 2013 - Posters’ Extended Abstracts. HCI 2013. Communications in Computer and Information Science, vol 374. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39476-8_83
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DOI: https://doi.org/10.1007/978-3-642-39476-8_83
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