Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Ou, Wenwu"'
Autor:
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 retrieval (IR) and search engines (SE). Recently, an additional post-ranking stage is suggested i
Externí odkaz:
http://arxiv.org/abs/2411.01178
Autor:
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 of short-video platforms, exemplified by TikTok and Kuaishou, the question arises: can perso
Externí odkaz:
http://arxiv.org/abs/2409.11281
Autor:
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 historical interactions. Achieving high-quality performance in SR requires attention to both ite
Externí odkaz:
http://arxiv.org/abs/2408.12153
Modern mobile applications heavily rely on the notification system to acquire daily active users and enhance user engagement. Being able to proactively reach users, the system has to decide when to send notifications to users. Although many researche
Externí odkaz:
http://arxiv.org/abs/2406.07067
Recommender systems are designed to learn user preferences from observed feedback and comprise many fundamental tasks, such as rating prediction and post-click conversion rate (pCVR) prediction. However, the observed feedback usually suffer from two
Externí odkaz:
http://arxiv.org/abs/2402.05740
Autor:
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 and language data. However, the prevailing approaches primarily regard the visual input as a
Externí odkaz:
http://arxiv.org/abs/2309.04669
Time series forecasting (TSF) is fundamentally required in many real-world applications, such as electricity consumption planning and sales forecasting. In e-commerce, accurate time-series sales forecasting (TSSF) can significantly increase economic
Externí odkaz:
http://arxiv.org/abs/2109.08381
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. Recently, researchers have found that the performance of CTR model can be improved greatly
Externí odkaz:
http://arxiv.org/abs/2108.04468
Reranking is attracting incremental attention in the recommender systems, which rearranges the input ranking list into the final rank-ing list to better meet user demands. Most existing methods greedily rerank candidates through the rating scores fro
Externí odkaz:
http://arxiv.org/abs/2104.00860
Recommender systems play a vital role in modern online services, such as Amazon and Taobao. Traditional personalized methods, which focus on user-item (UI) relations, have been widely applied in industrial settings, owing to their efficiency and effe
Externí odkaz:
http://arxiv.org/abs/2103.00442