insurance recommendation

DataFunTalk

Apr 28, 2023 · Artificial Intelligence

Causal Inference and Uplift Modeling for Insurance Recommendation and Explainability

This article explains how uplift sensitivity prediction, Bayesian causal networks, and decision‑path construction are applied to improve insurance product, coupon, and copy recommendations on the Fliggy platform, detailing modeling approaches, evaluation metrics, and practical outcomes of the causal inference framework.

AB testingbayesian networkscausal inference

0 likes · 16 min read

Causal Inference and Uplift Modeling for Insurance Recommendation and Explainability

DataFunTalk

Feb 28, 2023 · Artificial Intelligence

Event‑Aware Graph Extraction and Adaptive Clustering‑Gain Network for Insurance Creative Recommendation

This article presents a comprehensive study on insurance creative recommendation, introducing an event‑aware graph extractor, a heterogeneous graph construction, and an adaptive clustering‑gain network that together address data sparsity, counterfactual samples, and cross‑industry cold‑start challenges, achieving significant AUC improvements in experiments.

AIClusteringadvertising

0 likes · 15 min read

Event‑Aware Graph Extraction and Adaptive Clustering‑Gain Network for Insurance Creative Recommendation