2023
DOI: 10.48550/arxiv.2302.03883
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Multimodal Recommender Systems: A Survey

Abstract: The recommender system (RS) has been an integral toolkit of online services. They are equipped with various deep learning techniques to model user preference based on identifier and attribute information. With the emergence of multimedia services, such as short video, news and etc., understanding these contents while recommending becomes critical. Besides, multimodal features are also helpful in alleviating the problem of data sparsity in RS. Thus, Multimodal Recommender System (MRS) has attracted much attenti… Show more

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Cited by 2 publications
(1 citation statement)
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“…However, existing methods [14] of analyzing different types of side information by extracting features from different modalities by deep learning models or combining the multi-modal and user-item bipartite graph have not explored deeply about the relationship between user preference and side information. Even though the user-item bipartite graph contains the interaction data, this type of method does not contain the implicit relationships between interactions and side information.…”
Section: Introductionmentioning
confidence: 99%
“…However, existing methods [14] of analyzing different types of side information by extracting features from different modalities by deep learning models or combining the multi-modal and user-item bipartite graph have not explored deeply about the relationship between user preference and side information. Even though the user-item bipartite graph contains the interaction data, this type of method does not contain the implicit relationships between interactions and side information.…”
Section: Introductionmentioning
confidence: 99%