1 code implementation • 26 Jun 2022 • Xiaochuan Fan, Chi Zhang, Yong Yang, Yue Shang, Xueying Zhang, Zhen He, Yun Xiao, Bo Long, Lingfei Wu
For a platform with billions of products, it is extremely time-costly and labor-expensive to manually pick and organize qualified images.
no code implementations • 15 Jun 2022 • Zhizhi Yu, Di Jin, Jianguo Wei, Ziyang Liu, Yue Shang, Yun Xiao, Jiawei Han, Lingfei Wu
Graph Neural Networks (GNNs) have gained great popularity in tackling various analytical tasks on graph-structured data (i. e., networks).
1 code implementation • WWW 2022 • Jiashu Pu, Jianshi Lin, Xiaoxi Mao, Jianrong Tao, Xudong Shen, Yue Shang, Runze Wu
Players of online games generate rich behavioral data during gaming.
no code implementations • SIGIR 2021 • Xueying Zhang, Yunjiang Jiang, Yue Shang, Zhaomeng Cheng, Chi Zhang, Xiaochuan Fan, Yun Xiao, Bo Long
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 mobile display. First, we adopt a decoder-only transformer architecture, which fitswell for fine-tuning tasks by combining input and output all to-gether.
1 code implementation • 18 Oct 2021 • Kai Wang, Zhene Zou, Minghao Zhao, Qilin Deng, Yue Shang, Yile Liang, Runze Wu, Xudong Shen, Tangjie Lyu, Changjie Fan
In summary, the RL4RS (Reinforcement Learning for Recommender Systems), a new resource with special concerns on the reality gaps, contains two real-world datasets, data understanding tools, tuned simulation environments, related advanced RL baselines, batch RL baselines, and counterfactual policy evaluation algorithms.
no code implementations • 26 Apr 2021 • Yunjiang Jiang, Yue Shang, Rui Li, Wen-Yun Yang, Guoyu Tang, Chaoyi Ma, Yun Xiao, Eric Zhao
We describe a highly-scalable feed-forward neural model to provide relevance score for (query, item) pairs, using only user query and item title as features, and both user click feedback as well as limited human ratings as labels.
no code implementations • 13 Jan 2021 • Ziyang Liu, Zhaomeng Cheng, Yunjiang Jiang, Yue Shang, Wei Xiong, Sulong Xu, Bo Long, Di Jin
We propose in this paper a novel Second-order Relevance, which is fundamentally different from the previous First-order Relevance, to improve result relevance prediction.
no code implementations • 20 Oct 2020 • Yunjiang Jiang, Yue Shang, Ziyang Liu, Hongwei Shen, Yun Xiao, Wei Xiong, Sulong Xu, Weipeng Yan, Di Jin
Relevance has significant impact on user experience and business profit for e-commerce search platform.
no code implementations • 21 Aug 2020 • Yunjiang Jiang, Yue Shang, Hongwei Shen, Wen-Yun Yang, Yun Xiao
The quality of non-default ranking on e-commerce platforms, such as based on ascending item price or descending historical sales volume, often suffers from acute relevance problems, since the irrelevant items are much easier to be exposed at the top of the ranking results.
1 code implementation • 19 Dec 2018 • Zheng Chen, Yong Zhang, Yue Shang, Xiaohua Hu
TSPRA combines topics (i. e. product aspects), word sentiment and user preference as regression factors, and is able to perform topic clustering, review rating prediction, sentiment analysis and what we invent as "critical aspect" analysis altogether in one framework.