Advances in knowledge discovery and data mining aaai press mit press google scholar digital library 10 goldberg d nichols d oki b m and terry d 1992 l h and foster d p 1998 clustering methods for collaborative filtering in workshop on recommender systems at the 15th national conference onartificial intelligence.

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Knowledge graphs enable a wide variety of applications including question answering and information retrieval despite the great effort invested in their creation and maintenance even the largest e g yago dbpedia or wikidata remain incomplete we introduce relational graph convolutional networks r gcns and apply them to two standard knowledge.

We propose a simple yet effective approach for spatiotemporal feature learning using deep 3 dimensional convolutional networks 3d convnets trained on a large scale supervised video dataset our findings are three fold 1 3d convnets are more suitable for spatiotemporal feature learning compared to 2d convnets 2 a homogeneous architecture.

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