24 citations · 87 across the 20 of their papers we have counts for
9 papers · 1 filter
Intelligent Online Selling Point Extraction for E-Commerce Recommendation
Xiaojie Guo, Shugen Wang, Hanqing Zhao +8
In the past decade, automatic product description generation for e-commerce have witnessed significant advancement. As the services provided by e-commerce platforms become diverse,…
Automatic Product Copywriting for E-Commerce
Xueying Zhang, Yanyan Zou, Hainan Zhang +10
Product copywriting is a critical component of e-commerce recommendation platforms. It aims to attract users' interest and improve user experience by highlighting product character…
DSGPT: Domain-Specific Generative Pre-Training of Transformers for Text Generation in E-commerce Title and Review Summarization
Xueying Zhang, Yunjiang Jiang, Yue Shang +5
We propose a novel domain-specific generative pre-training (DS-GPT) method for text generation and apply it to the product titleand review summarization problems on E-commerce mobi…
SearchGCN: Powering Embedding Retrieval by Graph Convolution Networks for E-Commerce Search
Xinlin Xia, Shang Wang, Han Zhang +5
Graph convolution networks (GCN), which recently becomes new state-of-the-art method for graph node classification, recommendation and other applications, has not been successfully…
Joint Learning of Deep Retrieval Model and Product Quantization based Embedding Index
Han Zhang, Hongwei Shen, Yiming Qiu +6
Embedding index that enables fast approximate nearest neighbor(ANN) search, serves as an indispensable component for state-of-the-art deep retrieval systems. Traditional approaches…
Person Search Challenges and Solutions: A Survey
Xiangtan Lin, Pengzhen Ren, Yun Xiao +2
Person search has drawn increasing attention due to its real-world applications and research significance. Person search aims to find a probe person in a gallery of scene images wi…
A unified Neural Network Approach to E-CommerceRelevance Learning
Yunjiang Jiang, Yue Shang, Rui Li +5
Result relevance scoring is critical to e-commerce search user experience. Traditional information retrieval methods focus on keyword matching and hand-crafted or counting-based nu…
From Semantic Retrieval to Pairwise Ranking: Applying Deep Learning in E-commerce Search
Rui Li, Yunjiang Jiang, Wenyun Yang +7
We introduce deep learning models to the two most important stages in product search at JD.com, one of the largest e-commerce platforms in the world. Specifically, we outline the d…
Query Rewriting via Cycle-Consistent Translation for E-Commerce Search
Yiming Qiu, Kang Zhang, Han Zhang +5
Nowadays e-commerce search has become an integral part of many people's shopping routines. One critical challenge in today's e-commerce search is the semantic matching problem wher…