Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Bian, Shuqing"'
There is a rapidly-growing research interest in modeling user preferences via pre-training multi-domain interactions for recommender systems. However, Existing pre-trained multi-domain recommendations mostly select the item texts to be bridges across
Externí odkaz:
http://arxiv.org/abs/2311.01831
Autor:
Zhao, Wayne Xin, Hou, Yupeng, Pan, Xingyu, Yang, Chen, Zhang, Zeyu, Lin, Zihan, Zhang, Jingsen, Bian, Shuqing, Tang, Jiakai, Sun, Wenqi, Chen, Yushuo, Xu, Lanling, Zhang, Gaowei, Tian, Zhen, Tian, Changxin, Mu, Shanlei, Fan, Xinyan, Chen, Xu, Wen, Ji-Rong
In order to support the study of recent advances in recommender systems, this paper presents an extended recommendation library consisting of eight packages for up-to-date topics and architectures. First of all, from a data perspective, we consider t
Externí odkaz:
http://arxiv.org/abs/2206.07351
Autor:
Hou, Yupeng, Pan, Xingyu, Zhao, Wayne Xin, Bian, Shuqing, Song, Yang, Zhang, Tao, Wen, Ji-Rong
As the core technique of online recruitment platforms, person-job fit can improve hiring efficiency by accurately matching job positions with qualified candidates. However, existing studies mainly focus on the recommendation scenario, while neglectin
Externí odkaz:
http://arxiv.org/abs/2203.14232
Autor:
Bian, Shuqing, Chen, Xu, Zhao, Wayne Xin, Zhou, Kun, Hou, Yupeng, Song, Yang, Zhang, Tao, Wen, Ji-Rong
Publikováno v:
CIKM 2020
With the ever-increasing growth of online recruitment data, job-resume matching has become an important task to automatically match jobs with suitable resumes. This task is typically casted as a supervised text matching problem. Supervised learning i
Externí odkaz:
http://arxiv.org/abs/2009.13299
Conversational recommender systems (CRS) aim to recommend high-quality items to users through interactive conversations. Although several efforts have been made for CRS, two major issues still remain to be solved. First, the conversation data itself
Externí odkaz:
http://arxiv.org/abs/2007.04032
Autor:
Bian, Shuqing, Deng, Zhenpeng, Li, Fei, Monroe, Will, Shi, Peng, Sun, Zijun, Wu, Wei, Wang, Sikuang, Wang, William Yang, Yuan, Arianna, Zhang, Tianwei, Li, Jiwei
Cryptocurrencies (or digital tokens, digital currencies, e.g., BTC, ETH, XRP, NEO) have been rapidly gaining ground in use, value, and understanding among the public, bringing astonishing profits to investors. Unlike other money and banking systems,
Externí odkaz:
http://arxiv.org/abs/1803.03670