Zobrazeno 1 - 10
of 119
pro vyhledávání: '"Zhumin Chen"'
Autor:
Qingyao Ai, Ting Bai, Zhao Cao, Yi Chang, Jiawei Chen, Zhumin Chen, Zhiyong Cheng, Shoubin Dong, Zhicheng Dou, Fuli Feng, Shen Gao, Jiafeng Guo, Xiangnan He, Yanyan Lan, Chenliang Li, Yiqun Liu, Ziyu Lyu, Weizhi Ma, Jun Ma, Zhaochun Ren, Pengjie Ren, Zhiqiang Wang, Mingwen Wang, Ji-Rong Wen, Le Wu, Xin Xin, Jun Xu, Dawei Yin, Peng Zhang, Fan Zhang, Weinan Zhang, Min Zhang, Xiaofei Zhu
Publikováno v:
AI Open, Vol 4, Iss , Pp 80-90 (2023)
The research field of Information Retrieval (IR) has evolved significantly, expanding beyond traditional search to meet diverse user information needs. Recently, Large Language Models (LLMs) have demonstrated exceptional capabilities in text understa
Externí odkaz:
https://doaj.org/article/eb4eadd07c0a4203b546205d0388b406
Autor:
Wenchao Sun, Muyang Ma, Pengjie Ren, Yujie Lin, Zhumin Chen, Zhaochun Ren, Jun Ma, Maarten de Rijke
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 35:4106-4123
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0a4b22e2620a157db98d193921a6c2c7
https://doi.org/10.1109/tkde.2021.3130927
https://doi.org/10.1109/tkde.2021.3130927
Autor:
WEIWEI SUN1, SHUYU GUO1, SHUO ZHANG2, PENGJIE REN1, ZHUMIN CHEN1, DE RIJKE, MAARTEN3, ZHAOCHUN REN1
Publikováno v:
ACM Transactions on Information Systems. Jan2024, Vol. 42 Issue 1, p1-29. 29p.
Autor:
Yujie Lin, Chenyang Wang, Zhumin Chen, Zhaochun Ren, Xin Xin, Qiang Yan, Maarten de Rijke, Xiuzhen Cheng, Pengjie Ren
Sequential recommendations aim to capture users' preferences from their historical interactions so as to predict the next item that they will interact with. Sequential recommendation methods usually assume that all items in a user's historical intera
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8e6806d61663aa1d4ad3418406de8e20
http://arxiv.org/abs/2303.02297
http://arxiv.org/abs/2303.02297
Autor:
Muyang Ma, Pengjie Ren, Zhumin Chen, Zhaochun Ren, Lifan Zhao, Peiyu Liu, Jun Ma, Maarten de Rijke
Publikováno v:
ACM Transactions on Knowledge Discovery from Data. 16:1-32
Cross-domain sequential recommendation is the task of predict the next item that the user is most likely to interact with based on past sequential behavior from multiple domains. One of the key challenges in cross-domain sequential recommendation is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::018533a594ed88bd8c06654c3131d151
https://doi.org/10.1145/3487331
https://doi.org/10.1145/3487331
Publikováno v:
ACM Transactions on Information Systems, 39(4):47. Association for Computing Machinery (ACM)
In this paper, we address the problem of answering complex information needs by conversing conversations with search engines, in the sense that users can express their queries in natural language, and directly receivethe information they need from a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d3e555bcce41b161c6cf497c97c3eeb5
https://doi.org/10.1145/3432726
https://doi.org/10.1145/3432726
Autor:
XIN XIN1 jiyuan@mail.sdu.edu.cn, JIYUAN YANG1 yang@mail.sdu.edu.cn, HANBING WANG1 hanbing.wang@mail.sdu.edu.cn, JUN MA1 majun@sdu.edu.cn, PENGJIE REN1 renpengjie@sdu.edu.cn, HENGLIANG LUO2 chenzhumin@sdu.edu.cn, XINLEI SHI2 zhaochun.ren@sdu.edu.cn, ZHUMIN CHEN1 luohengliang@meituan.com, ZHAOCHUN REN1 shixinlei@meituan.com
Publikováno v:
ACM Transactions on Information Systems. Jul2023, Vol. 41 Issue 3, p1-25. 25p.
Autor:
MUYANG MA1 muyang0331@gmail.com, PENGJIE REN1 jay.ren@outlook.com, ZHUMIN CHEN1 chenzhumin@sdu.edu.cn, ZHAOCHUN REN1 zhaochun.ren@sdu.edu.cn, HUASHENG LIANG2 watsonliang@tencent.com, JUN MA1 majun@sdu.edu.cn, DE RIJKE, MAARTEN3 m.derijke@uva.nl
Publikováno v:
ACM Transactions on Information Systems. Jul2023, Vol. 41 Issue 3, p1-24. 24p.
Autor:
Zihan Wang, Na Huang, Fei Sun, Pengjie Ren, Zhumin Chen, Hengliang Luo, Maarten de Rijke, Zhaochun Ren
Publikováno v:
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
Learned recommender systems may inadvertently leak information about their training data, leading to privacy violations. We investigate privacy threats faced by recommender systems through the lens of membership inference. In such attacks, an adversa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ec5536e04255622570f10c06f56e0f61
https://doi.org/10.1145/3534678.3539392
https://doi.org/10.1145/3534678.3539392
Autor:
Zhaochun Ren, Zhi Tian, Dongdong Li, Pengjie Ren, Liu Yang, Xin Xin, Huasheng Liang, Maarten de Rijke, Zhumin Chen
Publikováno v:
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::628acbc4fdf690a765eb8990d04ed43e
https://doi.org/10.1145/3477495.3532077
https://doi.org/10.1145/3477495.3532077