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Joint user mention behavior modeling for mentionee recommendation

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成果类型:
期刊论文
作者:
Tang, Xiaoyue;Zhang, Cong*;Meng, Weiyi;Wang, Kai
通讯作者:
Zhang, Cong
作者机构:
[Zhang, Cong; Tang, Xiaoyue] Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430023, Peoples R China.
[Meng, Weiyi] Binghamton Univ, Dept Comp Sci, Binghamton, NY 13902 USA.
[Wang, Kai] Wuhan Univ, Sch Comp Sci, Wuhan 430072, Peoples R China.
通讯机构:
[Zhang, Cong] W
Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430023, Peoples R China.
语种:
英文
关键词:
Mentionee recommendation;User mention behavior;Joint Latent-class model
期刊:
Applied Intelligence
ISSN:
0924-669X
年:
2020
卷:
50
期:
8
页码:
2449-2464
基金类别:
This work is supported by the National Natural Science Foundation of China (No. 61272278), the Nature Science Foundation of Hubei Province (No. 2019CFB250), the Research Program of Hubei Provincial Department of Education (No. B2019060), and the Special Projects for Technological Innovation of Hubei Province (No. 2018ABA099).
机构署名:
本校为第一且通讯机构
院系归属:
数学与计算机学院
摘要:
As an emerging online interaction service in Twitter-like social media systems, mention serves to significantly improve both user interaction experience and information propagation. In recent years, the problem of mentionee recommendation, i.e., recommending mentionees (mentioned users) when mentioners (mentioning users) mention others, has received considerable attention. However, the extreme sparsity of mentioner-mentionee matrix creates a severe challenge. While an increasing line of work has exploited diverse effects such as the textual con...

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