11 citations · 21 across the 4 of their papers we have counts for
4 papers
A Multi-Granularity Matching Attention Network for Query Intent Classification in E-commerce Retrieval
Chunyuan Yuan, Yiming Qiu, Mingming Li +3
Query intent classification, which aims at assisting customers to find desired products, has become an essential component of the e-commerce search. Existing query intent classific…
Learning Multi-Stage Multi-Grained Semantic Embeddings for E-Commerce Search
Binbin Wang, Mingming Li, Zhixiong Zeng +5
Retrieving relevant items that match users' queries from billion-scale corpus forms the core of industrial e-commerce search systems, in which embedding-based retrieval (EBR) metho…
ZhichunRoad at Amazon KDD Cup 2022: MultiTask Pre-Training for E-Commerce Product Search
Xuange Cui, Wei Xiong, Songlin Wang
In this paper, we propose a robust multilingual model to improve the quality of search results. Our model not only leverage the processed class-balanced dataset, but also benefit f…
Pre-training Tasks for User Intent Detection and Embedding Retrieval in E-commerce Search
Yiming Qiu, Chenyu Zhao, Han Zhang +7
BERT-style models pre-trained on the general corpus (e.g., Wikipedia) and fine-tuned on specific task corpus, have recently emerged as breakthrough techniques in many NLP tasks: qu…