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This tutorial aims to explore methods for improving recommender systems by utilizing multiple data types or modalities.

September 13, 2021Open Access

Multi-Modal Recommender Systems: Hands-On Exploration

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This tutorial aims to explore methods for improving recommender systems by utilizing multiple data types or modalities.
Reviewed recent advances in multi-modal recommendation techniques.
Conducted hands-on sessions using Cornac framework for practical application.
Compared various models and modalities to assess their impacts on user-item recommendations.
Demonstrated the effectiveness of incorporating auxiliary information to mitigate data sparsity.
Highlighted the significance of different modalities in enhancing recommendation accuracy.

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Tutorial reviews recent advances in multi-modal recommender systems, emphasizing practical comparisons of methods and modalities.

Truong et al. (2021) studied this question.

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