Incorporating Joint Embeddings into Goal-Oriented Dialogues with Multi-Task Learning

1 code implementation • 28 Jan 2020 • Firas Kassawat, Debanjan Chaudhuri, Jens Lehmann

Since such models can greatly benefit from user intent and knowledge graph integration, in this paper we propose an RNN-based end-to-end encoder-decoder architecture which is trained with joint embeddings of the knowledge graph and the corpus as input.

Decoder Goal-Oriented Dialog +3