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Multi-Modal Knowledge Representation Learning via Webly-Supervised Relationships Mining
2017
Proceedings of the 2017 ACM on Multimedia Conference - MM '17
Knowledge representation learning (KRL) encodes enormous structured information with entities and relations into a continuous low-dimensional semantic space. Most conventional methods solely focus on learning knowledge representation from single modality, yet neglect the complementary information from others. The more and more rich available multi-modal data on Internet also drive us to explore a novel approach for KRL in multi-modal way, and overcome the limitations of previous single-modal
doi:10.1145/3123266.3123443
dblp:conf/mm/NianBLX17
fatcat:e5wyg4iykzgexcb6vohf2okshm