Recent studies try to build task-oriented dialogue system in an end-to-end manner and the existing works make great progress on this task. However, there are still two issues need to consider: (1) How to effectively represent the knowledge bases and incorporate it into dialogue system. (2) How to efficiently reason the knowledge bases given queries. To solve these issues , we design a novel Transformer-based Dynamic Memory Network (DMN) with a novel Memory Mask scheme , which can dynamically generate the context-aware knowledge base representations , and reason the knowledge bases simultaneously . Furthermore, we incorporate the dynamic memory network into Transformer and propose Dynamic Memory Enhanced Transformer ( DMET ), which can aggregate information from  dialogue history and knowledge bases to generate better responses. Through extensive experiments, our method can achieve superior performance over the state-of-the-art methods.
Recent studies try to build task-oriented dialogue systems in an end-to-end manner and the existing works make great progress on this task. However, there is still an issue need to be further considered, i.e., how to effectively represent the knowledge bases and incorporate that into dialogue systems. To solve this issue , we design a novel Context-aware Memory Generation module to model the knowledge bases , which can generate context-aware entity representations with perceiving relevant entities . Furthermore, we incorporate this module into Transformer and propose Context-aware Memory Enhanced Transformer ( CMET ), which can aggregate information from the dialogue history and knowledge bases to generate better responses. Through extensive experiments, our method can achieve superior performance over the state-of-the-art methods.
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system
systems
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are still two issues need to consider: (1) How
is still an issue need to be further considered, i.e., how
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it into dialogue system. (2) How to efficiently reason the knowledge bases given queries. To solve these issues
that into dialogue systems. To solve this issue
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Transformer-based Dynamic Memory Network (DMN) with a novel Memory Mask scheme
Context-aware Memory Generation module to model the knowledge bases
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dynamically generate the
generate
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knowledge base representations , and reason the knowledge bases simultaneously
entity representations with perceiving relevant entities
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the dynamic memory network
this module
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Dynamic
Context-aware
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DMET
CMET
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the