402 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Alibaba Group (China)CN60 papers
- Zhejiang UniversityCN46 papers
- Bellevue Hospital CenterUS30 papers
- Peking UniversityCN22 papers
- Nanyang Technological UniversitySG21 papers
- Tsinghua UniversityCN15 papers
- Chinese Academy of SciencesCN14 papers
- Renmin University of ChinaCN13 papers
- Shanghai Jiao Tong UniversityCN11 papers
- Tianjin UniversityCN11 papers
- Alibaba Group (Cayman Islands)KY10 papers
- East China Normal UniversityCN10 papers
15 papers · 1 filter
LORE: A Large Generative Model for Search Relevance
Chenji Lu, Zhuo Chen, Hui Zhao +9
Achievement. We introduce LORE, a systematic framework for Large Generative Model-based relevance in e-commerce search. Deployed and iterated over three years, LORE achieves a cumu…
TaoSR1: The Thinking Model for E-commerce Relevance Search
Chenhe Dong, Shaowei Yao, Pengkun Jiao +7
Query-product relevance prediction is a core task in e-commerce search. BERT-based models excel at semantic matching but lack complex reasoning capabilities. While Large Language M…
Dynamic Sequential Graph Learning for Click-Through Rate Prediction
Yunfei Chu, Xiaofu Chang, Kunyang Jia +2
Click-through rate prediction plays an important role in the field of recommender system and many other applications. Existing methods mainly extract user interests from user histo…
LHRM: A LBS based Heterogeneous Relations Model for User Cold Start Recommendation in Online Travel Platform
Ziyi Wang, Wendong Xiao, Yu Li +2
Most current recommender systems used the historical behaviour data of user to predict user' preference. However, it is difficult to recommend items to new users accurately. To all…
Unified Conversational Recommendation Policy Learning via Graph-based Reinforcement Learning
Yang Deng, Yaliang Li, Fei Sun +2
Conversational recommender systems (CRS) enable the traditional recommender systems to explicitly acquire user preferences towards items and attributes through interactive conversa…
Explore User Neighborhood for Real-time E-commerce Recommendation
Xu Xie, Fei Sun, Xiaoyong Yang +4
Recommender systems play a vital role in modern online services, such as Amazon and Taobao. Traditional personalized methods, which focus on user-item (UI) relations, have been wid…
Learning a Product Relevance Model from Click-Through Data in E-Commerce
Shaowei Yao, Jiwei Tan, Xi Chen +4
The search engine plays a fundamental role in online e-commerce systems, to help users find the products they want from the massive product collections. Relevance is an essential r…
ICS-Assist: Intelligent Customer Inquiry Resolution Recommendation in Online Customer Service for Large E-Commerce Businesses
Min Fu, Jiwei Guan, Xi Zheng +6
Efficient and appropriate online customer service is essential to large e-commerce businesses. Existing solution recommendation methods for online customer service are unable to de…
Disentangled Item Representation for Recommender Systems
Zeyu Cui, Feng Yu, Shu Wu +2
Item representations in recommendation systems are expected to reveal the properties of items. Collaborative recommender methods usually represent an item as one single latent vect…
Sequential Recommendation with Self-Attentive Multi-Adversarial Network
Ruiyang Ren, Zhaoyang Liu, Yaliang Li +4
Recently, deep learning has made significant progress in the task of sequential recommendation. Existing neural sequential recommenders typically adopt a generative way trained wit…
Graph Neural News Recommendation with Long-term and Short-term Interest Modeling
Linmei Hu, Chen Li, Chuan Shi +2
With the information explosion of news articles, personalized news recommendation has become important for users to quickly find news that they are interested in. Existing methods…
Multi-Interest Network with Dynamic Routing for Recommendation at Tmall
Chao Li, Zhiyuan Liu, Mengmeng Wu +7
Industrial recommender systems usually consist of the matching stage and the ranking stage, in order to handle the billion-scale of users and items. The matching stage retrieves ca…
Graph Convolution for Multimodal Information Extraction from Visually Rich Documents
Xiaojing Liu, Feiyu Gao, Qiong Zhang +1
Visually rich documents (VRDs) are ubiquitous in daily business and life. Examples are purchase receipts, insurance policy documents, custom declaration forms and so on. In VRDs, v…
Globally Optimized Mutual Influence Aware Ranking in E-Commerce Search
Tao Zhuang, Wenwu Ou, Zhirong Wang
In web search, mutual influences between documents have been studied from the perspective of search result diversification. But the methods in web search is not directly applicable…
A General SIMD-based Approach to Accelerating Compression Algorithms
Wayne Xin Zhao, Xudong Zhang, Daniel Lemire +4
Compression algorithms are important for data oriented tasks, especially in the era of Big Data. Modern processors equipped with powerful SIMD instruction sets, provide us an oppor…