Densifying Knowledge Hypergraphs with LLM-based review distillation for conversational consumer decision support

• Review-driven structural induction alleviates sparsity in conversational recommendation. • LLM-distilled review semantics are grounded as entities to densify hypergraph structures. • Item-centric hypergraph learning supports joint recommendation and response generation. • Two-stage training stabilizes structure learning under sparse conversational supervision.