User interest-based recommender system for image-sharing social media
Autor: | Jongmo Kim, Kunyoung Kim, Minhwan Kim, Mye M. Sohn |
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Rok vydání: | 2020 |
Předmět: |
Topic model
Information retrieval Computer Networks and Communications Computer science Image sharing 02 engineering and technology Recommender system Latent Dirichlet allocation Graph symbols.namesake Hardware and Architecture 020204 information systems 0202 electrical engineering electronic engineering information engineering symbols 020201 artificial intelligence & image processing Social media Software |
Zdroj: | World Wide Web. 24:1003-1025 |
ISSN: | 1573-1413 1386-145X |
Popis: | Nowadays, many people use social media to communicate with others, share their interests and obtain information. As the performance of the embedded cameras on mobile phones improve, image-sharing social media became a popular tool for people to communicate with others and share their interests, which yields vast amount of data related to the users’ interests. However, only few studies pay attention to analyze data in image-sharing social media and utilize it to perform appropriate services, such as recommendation. We propose a framework to discover user interests using the Latent Dirichlet Allocation (LDA) based topic model and to recommend protentional friends and POIs related to the target user’s interests. To do this, we devise the advanced LDA based topic model which can be utilized in image-sharing social media by exploiting both textual features and visual features. In addition, the novel method to discover user interest is proposed by generating topic graph to represent the user interest as graph-shape, which is an effective way to completely describe the user interest as explicit form. Lastly, we propose a method to recommend POIs and potential friends to the target user by calculating graph similarity between topic graphs. To demonstrate the superiority of our framework, we collected real data from image-sharing social media and conducted comparison experiments with state-of-the-art methods. |
Databáze: | OpenAIRE |
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