41 citations · 51 across the 7 of their papers we have counts for
7 papers
Delving into E-Commerce Product Retrieval with Vision-Language Pre-training
Xiaoyang Zheng, Fuyu Lv, Zilong Wang +2
E-commerce search engines comprise a retrieval phase and a ranking phase, where the first one returns a candidate product set given user queries. Recently, vision-language pre-trai…
Cold-Start based Multi-Scenario Ranking Model for Click-Through Rate Prediction
Peilin Chen, Hong Wen, Jing Zhang +6
Online travel platforms (OTPs), e.g., Ctrip.com or Fliggy.com, can effectively provide travel-related products or services to users. In this paper, we focus on the multi-scenario c…
Re-weighting Negative Samples for Model-Agnostic Matching
Jiazhen Lou, Hong Wen, Fuyu Lv +3
Recommender Systems (RS), as an efficient tool to discover users' interested items from a very large corpus, has attracted more and more attention from academia and industry. As th…
Deep Interest Highlight Network for Click-Through Rate Prediction in Trigger-Induced Recommendation
Qijie Shen, Hong Wen, Wanjie Tao +4
In many classical e-commerce platforms, personalized recommendation has been proven to be of great business value, which can improve user satisfaction and increase the revenue of p…
Modeling User Behavior with Graph Convolution for Personalized Product Search
Fan Lu, Qimai Li, Bo Liu +7
User preference modeling is a vital yet challenging problem in personalized product search. In recent years, latent space based methods have achieved state-of-the-art performance b…
IHGNN: Interactive Hypergraph Neural Network for Personalized Product Search
Dian Cheng, Jiawei Chen, Wenjun Peng +5
A good personalized product search (PPS) system should not only focus on retrieving relevant products, but also consider user personalized preference. Recent work on PPS mainly ado…
Multi-Level Deep Cascade Trees for Conversion Rate Prediction in Recommendation System
Hong Wen, Jing Zhang, Quan Lin +2
Developing effective and efficient recommendation methods is very challenging for modern e-commerce platforms. Generally speaking, two essential modules named "Click-Through Rate P…