227 citations · 461 across the 14 of their papers we have counts for
14 papers
Beyond Matching: Category-Guided Latent Intent Reasoning for Generative Retrieval in E-Commerce
Fuwei Zhang, Xiaoyu Liu, Jiajie Jin +8
Generative retrieval offers a new paradigm for e-commerce search by mapping user queries directly to product Semantic Identifiers (SIDs). However, e-commerce queries are often shor…
Multi-Aspect Cross-modal Quantization for Generative Recommendation
Fuwei Zhang, Xiaoyu Liu, Dongbo Xi +5
Generative Recommendation (GR) has emerged as a new paradigm in recommender systems. This approach relies on quantized representations to discretize item features, modeling users'…
Large-Scale Multi-Domain Recommendation: an Automatic Domain Feature Extraction and Personalized Integration Framework
Dongbo Xi, Zhen Chen, Yuexian Wang +4
Feed recommendation is currently the mainstream mode for many real-world applications (e.g., TikTok, Dianping), it is usually necessary to model and predict user interests in multi…
Modeling Users' Behavior Sequences with Hierarchical Explainable Network for Cross-domain Fraud Detection
Yongchun Zhu, Dongbo Xi, Bowen Song +4
With the explosive growth of the e-commerce industry, detecting online transaction fraud in real-world applications has become increasingly important to the development of e-commer…
Exploiting Bi-directional Global Transition Patterns and Personal Preferences for Missing POI Category Identification
Dongbo Xi, Fuzhen Zhuang, Yanchi Liu +4
Recent years have witnessed the increasing popularity of Location-based Social Network (LBSN) services, which provides unparalleled opportunities to build personalized Point-of-Int…
Neural Hierarchical Factorization Machines for User's Event Sequence Analysis
Dongbo Xi, Fuzhen Zhuang, Bowen Song +6
Many prediction tasks of real-world applications need to model multi-order feature interactions in user's event sequence for better detection performance. However, existing popular…
Domain Adaptation with Category Attention Network for Deep Sentiment Analysis
Dongbo Xi, Fuzhen Zhuang, Ganbin Zhou +3
Domain adaptation tasks such as cross-domain sentiment classification aim to utilize existing labeled data in the source domain and unlabeled or few labeled data in the target doma…
Modelling of Bi-directional Spatio-Temporal Dependence and Users' Dynamic Preferences for Missing POI Check-in Identification
Dongbo Xi, Fuzhen Zhuang, Yanchi Liu +3
Human mobility data accumulated from Point-of-Interest (POI) check-ins provides great opportunity for user behavior understanding. However, data quality issues (e.g., geolocation i…
Modeling the Sequential Dependence among Audience Multi-step Conversions with Multi-task Learning in Targeted Display Advertising
Dongbo Xi, Zhen Chen, Peng Yan +4
In most real-world large-scale online applications (e.g., e-commerce or finance), customer acquisition is usually a multi-step conversion process of audiences. For example, an impr…
Transfer-Meta Framework for Cross-domain Recommendation to Cold-Start Users
Yongchun Zhu, Kaikai Ge, Fuzhen Zhuang +5
Cold-start problems are enormous challenges in practical recommender systems. One promising solution for this problem is cross-domain recommendation (CDR) which leverages rich info…
Modeling the Field Value Variations and Field Interactions Simultaneously for Fraud Detection
Dongbo Xi, Bowen Song, Fuzhen Zhuang +5
With the explosive growth of e-commerce, online transaction fraud has become one of the biggest challenges for e-commerce platforms. The historical behaviors of users provide rich…
Graph Factorization Machines for Cross-Domain Recommendation
Dongbo Xi, Fuzhen Zhuang, Yongchun Zhu +3
Recently, graph neural networks (GNNs) have been successfully applied to recommender systems. In recommender systems, the user's feedback behavior on an item is usually the result…
Transfer Learning Toolkit: Primers and Benchmarks
Fuzhen Zhuang, Keyu Duan, Tongjia Guo +4
The transfer learning toolkit wraps the codes of 17 transfer learning models and provides integrated interfaces, allowing users to use those models by calling a simple function. It…
A Comprehensive Survey on Transfer Learning
Fuzhen Zhuang, Zhiyuan Qi, Keyu Duan +5
Transfer learning aims at improving the performance of target learners on target domains by transferring the knowledge contained in different but related source domains. In this wa…