Multimodal Topic Learning for Video Recommendation

no code implementations • 26 Oct 2020 • Shi Pu, Yijiang He, Zheng Li, Mao Zheng

Existing video recommendation systems directly exploit features from different modalities (e. g., user personal data, user behavior data, video titles, video tags, and visual contents) to input deep neural networks, while expecting the networks to online mine user-preferred topics implicitly from these features.

Computational Efficiency Recommendation Systems