3 citations · 5 across the 3 of their papers we have counts for
5 papers
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…
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…