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4 papers · 2 filters
Explainable LLM-driven Multi-dimensional Distillation for E-Commerce Relevance Learning
Gang Zhao, Ximing Zhang, Chenji Lu +5
Effective query-item relevance modeling is pivotal for enhancing user experience and safeguarding user satisfaction in e-commerce search systems. Recently, benefiting from the vast…
FedUD: Exploiting Unaligned Data for Cross-Platform Federated Click-Through Rate Prediction
Wentao Ouyang, Rui Dong, Ri Tao +1
Click-through rate (CTR) prediction plays an important role in online advertising platforms. Most existing methods use data from the advertising platform itself for CTR prediction.…
Deep Bag-of-Words Model: An Efficient and Interpretable Relevance Architecture for Chinese E-Commerce
Zhe Lin, Jiwei Tan, Dan Ou +3
Text relevance or text matching of query and product is an essential technique for the e-commerce search system to ensure that the displayed products can match the intent of the qu…
Masked Multi-Domain Network: Multi-Type and Multi-Scenario Conversion Rate Prediction with a Single Model
Wentao Ouyang, Xiuwu Zhang, Chaofeng Guo +8
In real-world advertising systems, conversions have different types in nature and ads can be shown in different display scenarios, both of which highly impact the actual conversion…