Search Results - "Ou, Wenwu"

Explore User Neighborhood for Real-time E-commerce Recommendation by Xie, Xu, Sun, Fei, Yang, Xiaoyong, Yang, Zhao, Gao, Jinyang, Ou, Wenwu, Cui, Bin

“…Recommender systems play a vital role in modern online services, such as Amazon and Taobao. Traditional personalized methods, which focus on user-item (UI)…”
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Self-Propagation Graph Neural Network for Recommendation by Yu, Wenhui, Lin, Xiao, Liu, Jinfei, Ge, Junfeng, Ou, Wenwu, Qin, Zheng

“…In recommendation tasks, we model user preferences by learning node representations (i.e., user and item embeddings) based on the observed user-item…”
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Multi-Task Learning with Calibrated Mixture of Insightful Experts by Wang, Sinan, Li, Yumeng, Li, Hongyan, Zhu, Tanchao, Li, Zhao, Ou, Wenwu

“…Multi-task learning has been established as an important machine learning framework for leveraging shared knowledge among multiple different but related tasks,…”
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Beyond Relevance: Improving User Engagement by Personalization for Short-Video Search by Bao, Wentian, Liu, Hu, Zheng, Kai, Zhang, Chao, Zhang, Shunyu, Yu, Enyun, Ou, Wenwu, Song, Yang

“…Personalized search has been extensively studied in various applications, including web search, e-commerce, social networks, etc. With the soaring popularity…”
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CounterCLR: Counterfactual Contrastive Learning with Non-random Missing Data in Recommendation by Wang, Jun, Li, Haoxuan, Zhang, Chi, Liang, Dongxu, Yu, Enyun, Ou, Wenwu, Wang, Wenjia

“…Recommender systems are designed to learn user preferences from observed feedback and comprise many fundamental tasks, such as rating prediction and post-click…”
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TIM: Temporal Interaction Model in Notification System by Ji, Huxiao, Yang, Haitao, Li, Linchuan, Zhang, Shunyu, Zhang, Cunyi, Li, Xuanping, Ou, Wenwu

“…Modern mobile applications heavily rely on the notification system to acquire daily active users and enhance user engagement. Being able to proactively reach…”
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CounterCLR: Counterfactual Contrastive Learning with Non-random Missing Data in Recommendation by Wang, Jun, Li, Haoxuan, Zhang, Chi, Liang, Dongxu, Yu, Enyun, Ou, Wenwu, Wang, Wenjia

“…Recommender systems are designed to learn user preferences from observed feedback and comprise many fundamental tasks, such as rating prediction and post-click…”
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LLM4PR: Improving Post-Ranking in Search Engine with Large Language Models by Yan, Yang, Wang, Yihao, Zhang, Chi, Hou, Wenyuan, Pan, Kang, Ren, Xingkai, Wu, Zelun, Zhai, Zhixin, Yu, Enyun, Ou, Wenwu, Song, Yang

“…Alongside the rapid development of Large Language Models (LLMs), there has been a notable increase in efforts to integrate LLM techniques in information…”
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DimeRec: A Unified Framework for Enhanced Sequential Recommendation via Generative Diffusion Models by Li, Wuchao, Huang, Rui, Zhao, Haijun, Liu, Chi, Zheng, Kai, Liu, Qi, Mou, Na, Zhou, Guorui, Lian, Defu, Song, Yang, Bao, Wentian, Yu, Enyun, Ou, Wenwu

“…Sequential Recommendation (SR) plays a pivotal role in recommender systems by tailoring recommendations to user preferences based on their non-stationary…”
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Revisit Recommender System in the Permutation Prospective by Feng, Yufei, Gong, Yu, Sun, Fei, Ge, Junfeng, Ou, Wenwu

“…Recommender systems (RS) work effective at alleviating information overload and matching user interests in various web-scale applications. Most RS retrieve the…”
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Semi-supervised Collaborative Filtering by Text-enhanced Domain Adaptation by Yu, Wenhui, Lin, Xiao, Ge, Junfeng, Ou, Wenwu, Qin, Zheng

“…Data sparsity is an inherent challenge in the recommender systems, where most of the data is collected from the implicit feedbacks of users. This causes two…”
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Globally Optimized Mutual Influence Aware Ranking in E-Commerce Search by Zhuang, Tao, Ou, Wenwu, Wang, Zhirong

“…IJCAI 2018 In web search, mutual influences between documents have been studied from the perspective of search result diversification. But the methods in web…”
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From Known to Unknown: Knowledge-guided Transformer for Time-Series Sales Forecasting in Alibaba by Qi, Xinyuan, Hou, Kai, Liu, Tong, Yu, Zhongzhong, Hu, Sihao, Ou, Wenwu

“…Time series forecasting (TSF) is fundamentally required in many real-world applications, such as electricity consumption planning and sales forecasting. In…”
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End-to-End User Behavior Retrieval in Click-Through RatePrediction Model by Chen, Qiwei, Pei, Changhua, Lv, Shanshan, Li, Chao, Ge, Junfeng, Ou, Wenwu

“…Click-Through Rate (CTR) prediction is one of the core tasks in recommender systems (RS). It predicts a personalized click probability for each user-item pair…”
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Commonsense Knowledge Adversarial Dataset that Challenges ELECTRA by Lin, Gongqi, Miao, Yuan, Yang, Xiaoyong, Ou, Wenwu, Cui, Lizhen, Guo, Wei, Miao, Chunyan

“…Commonsense knowledge is critical in human reading comprehension. While machine comprehension has made significant progress in recent years, the ability in…”
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GRN: Generative Rerank Network for Context-wise Recommendation by Feng, Yufei, Hu, Binbin, Gong, Yu, Sun, Fei, Liu, Qingwen, Ou, Wenwu

“…Reranking is attracting incremental attention in the recommender systems, which rearranges the input ranking list into the final rank-ing list to better meet…”
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Explore User Neighborhood for Real-time E-commerce Recommendation by Xie, Xu, Sun, Fei, Yang, Xiaoyong, Yang, Zhao, Gao, Jinyang, Ou, Wenwu, Cui, Bin

“…Recommender systems play a vital role in modern online services, such as Amazon and Taobao. Traditional personalized methods, which focus on user-item (UI)…”
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Behavior Sequence Transformer for E-commerce Recommendation in Alibaba by Chen, Qiwei, Zhao, Huan, Li, Wei, Huang, Pipei, Ou, Wenwu

“…Deep learning based methods have been widely used in industrial recommendation systems (RSs). Previous works adopt an Embedding&MLP paradigm: raw features are…”
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Unified Language-Vision Pretraining in LLM with Dynamic Discrete Visual Tokenization by Jin, Yang, Xu, Kun, Chen, Liwei, Liao, Chao, Tan, Jianchao, Huang, Quzhe, Chen, Bin, Lei, Chenyi, Liu, An, Song, Chengru, Lei, Xiaoqiang, Zhang, Di, Ou, Wenwu, Gai, Kun, Mu, Yadong

“…Recently, the remarkable advance of the Large Language Model (LLM) has inspired researchers to transfer its extraordinary reasoning capability to both vision…”
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Compositional Network Embedding by Lyu, Tianshu, Sun, Fei, Jiang, Peng, Ou, Wenwu, Zhang, Yan

“…Network embedding has proved extremely useful in a variety of network analysis tasks such as node classification, link prediction, and network visualization…”
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