3 citations · 9 across the 8 of their papers we have counts for
8 papers
PANE-GNN: Unifying Positive and Negative Edges in Graph Neural Networks for Recommendation
Ziyang Liu, Chaokun Wang, Jingcao Xu +5
Recommender systems play a crucial role in addressing the issue of information overload by delivering personalized recommendations to users. In recent years, there has been a growi…
Knowledge Distillation based Contextual Relevance Matching for E-commerce Product Search
Ziyang Liu, Chaokun Wang, Hao Feng +2
Online relevance matching is an essential task of e-commerce product search to boost the utility of search engines and ensure a smooth user experience. Previous work adopts either…
TeKo: Text-Rich Graph Neural Networks with External Knowledge
Zhizhi Yu, Di Jin, Jianguo Wei +5
Graph Neural Networks (GNNs) have gained great popularity in tackling various analytical tasks on graph-structured data (i.e., networks). Typical GNNs and their variants follow a m…
RDU: A Region-based Approach to Form-style Document Understanding
Fengbin Zhu, Chao Wang, Wenqiang Lei +2
Key Information Extraction (KIE) is aimed at extracting structured information (e.g. key-value pairs) from form-style documents (e.g. invoices), which makes an important step towar…
Heterogeneous Network Embedding for Deep Semantic Relevance Match in E-commerce Search
Ziyang Liu, Zhaomeng Cheng, Yunjiang Jiang +5
Result relevance prediction is an essential task of e-commerce search engines to boost the utility of search engines and ensure smooth user experience. The last few years eyewitnes…
BERT2DNN: BERT Distillation with Massive Unlabeled Data for Online E-Commerce Search
Yunjiang Jiang, Yue Shang, Ziyang Liu +6
Relevance has significant impact on user experience and business profit for e-commerce search platform. In this work, we propose a data-driven framework for search relevance predic…
BiTe-GCN: A New GCN Architecture via BidirectionalConvolution of Topology and Features on Text-Rich Networks
Di Jin, Xiangchen Song, Zhizhi Yu +4
Graph convolutional networks (GCNs), aiming to integrate high-order neighborhood information through stacked graph convolution layers, have demonstrated remarkable power in many ne…
Query Expansion Based on Clustered Results
Ziyang Liu, Sivaramakrishnan Natarajan, Yi Chen
Query expansion is a functionality of search engines that suggests a set of related queries for a user-issued keyword query. Typical corpus-driven keyword query expansion approache…