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Dialogue Generation for Conversational Recommendation Using User Search Interactions and Knowledge Graphs
Large-scale conversational recommendation datasets typically require manual dialogue construction or annotation. We propose SearCl, which automatically generates conversational recommendation dialogues grounded in user search and click behaviors. SearCl segments user interactions into query sessions
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