Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Leng, Dewei"'
Autor:
Si, Zihua, Guan, Lin, Sun, ZhongXiang, Zang, Xiaoxue, Lu, Jing, Hui, Yiqun, Cao, Xingchao, Yang, Zeyu, Zheng, Yichen, Leng, Dewei, Zheng, Kai, Zhang, Chenbin, Niu, Yanan, Song, Yang, Gai, Kun
The significance of modeling long-term user interests for CTR prediction tasks in large-scale recommendation systems is progressively gaining attention among researchers and practitioners. Existing work, such as SIM and TWIN, typically employs a two-
Externí odkaz:
http://arxiv.org/abs/2407.16357
Autor:
Shi, Teng, Si, Zihua, Xu, Jun, Zhang, Xiao, Zang, Xiaoxue, Zheng, Kai, Leng, Dewei, Niu, Yanan, Song, Yang
Nowadays, many platforms provide users with both search and recommendation services as important tools for accessing information. The phenomenon has led to a correlation between user search and recommendation behaviors, providing an opportunity to mo
Externí odkaz:
http://arxiv.org/abs/2404.09520
Autor:
Sun, Zhongxiang, Si, Zihua, Zang, Xiaoxue, Leng, Dewei, Niu, Yanan, Song, Yang, Zhang, Xiao, Xu, Jun
Publikováno v:
CIKM '23: Proceedings of the 32nd ACM International Conference on Information and Knowledge Management October 2023
The confluence of Search and Recommendation (S&R) services is vital to online services, including e-commerce and video platforms. The integration of S&R modeling is a highly intuitive approach adopted by industry practitioners. However, there is a no
Externí odkaz:
http://arxiv.org/abs/2306.07705
Autor:
Chang, Jianxin, Zhang, Chenbin, Fu, Zhiyi, Zang, Xiaoxue, Guan, Lin, Lu, Jing, Hui, Yiqun, Leng, Dewei, Niu, Yanan, Song, Yang, Gai, Kun
Life-long user behavior modeling, i.e., extracting a user's hidden interests from rich historical behaviors in months or even years, plays a central role in modern CTR prediction systems. Conventional algorithms mostly follow two cascading stages: a
Externí odkaz:
http://arxiv.org/abs/2302.02352
With the increase of content pages and interactive buttons in online services such as online-shopping and video-watching websites, industrial-scale recommender systems face challenges in multi-domain and multi-task recommendations. The core of multi-
Externí odkaz:
http://arxiv.org/abs/2302.01115