CR-Walker: Tree-Structured Graph Reasoning and Dialog Acts for Conversational Recommendation (2021.emnlp-main)
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| Challenge: | Existing systems that explore user preference through conversational interactions do not exploit the context and knowledge to make accurate recommendations. |
| Approach: | They propose a model that performs tree-structured reasoning on a knowledge graph and generates informative dialog acts to guide language generation. |
| Outcome: | The proposed model can arrive at more accurate recommendation and generate more informative and engaging responses. |
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