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Promoting Social Media Dissemination of Digital Images Through CBR-Based Tag Recommendation
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2022
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Martín Gómez, Lucía // Pérez Marcos, Javier // Cordero Gutiérrez, Rebeca // Hernandez de la Iglesia, Daniel
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UNIR
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1989-1660
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Gómez, Lucía Martín, Javier Pérez, Rebeca Cordero Gutiérrez, y Daniel H. de la Iglesia. «Promoting Social Media Dissemination of Digital Images Through CBR-Based Tag Recommendation». IJIMAI 7, n.º 6 (2022): 45-53. https://doi.org/10.9781/IJIMAI.2022.09.002.
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IJIMAI 7, n.º 6 (2022): 45-53. https://doi.org/10.9781/IJIMAI.2022.09.002.
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Multimedia content has become an essential tool to share knowledge, sell products or disseminate messages.
Some social networks use multimedia content to promote information and create social communities. In
order to increase the impact of the digital content, those images or videos are labeled with different words,
denominated tags. In this paper, we propose a recommender system which analyzes multimedia content
and suggests tags to maximize its influence in the social community. It implements a Case-Based Reasoning
architecture (CBR), which allows to learn from previous tagged content. The system has been evaluated
through cross fold validation with a training and validation sets carefully constructed and extracted from
Instagram. The results demonstrate that the system can suggest good options to label our image and maximize the influence of the multimedia content.
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