GARCIA: Powering Representations of Long-tail Query with Multi-granularity Contrastive Learning

no code implementations • 25 Apr 2023 • Weifan Wang, Binbin Hu, Zhicheng Peng, Mingjie Zhong, Zhiqiang Zhang, Zhongyi Liu, Guannan Zhang, Jun Zhou

At last, we conduct extensive experiments on both offline and online environments, which demonstrates the superior capability of GARCIA in improving tail queries and overall performance in service search scenarios.

Contrastive Learning Transfer Learning

DCMT: A Direct Entire-Space Causal Multi-Task Framework for Post-Click Conversion Estimation

no code implementations • 13 Feb 2023 • Feng Zhu, Mingjie Zhong, Xinxing Yang, Longfei Li, Lu Yu, Tiehua Zhang, Jun Zhou, Chaochao Chen, Fei Wu, Guanfeng Liu, Yan Wang

In recommendation scenarios, there are two long-standing challenges, i. e., selection bias and data sparsity, which lead to a significant drop in prediction accuracy for both Click-Through Rate (CTR) and post-click Conversion Rate (CVR) tasks.

counterfactual Multi-Task Learning +1