作者
Hao Gao, Yongqing Wang, Jiangli Shao, Huawei Shen, Xueqi Cheng
发表日期
2021/12/15
研讨会论文
2021 IEEE International Conference on Big Data (Big Data)
页码范围
607-613
出版商
IEEE
简介
User identity linkage aims to link users with the same identities across different social networks. Recently, re- searchers model the similarities of users’ behaviors such as Point of Interests(PoIs) or User Generated Contents(UGCs) to predict the identities of users. However, it is non-trivial to solve the problem due to the following challenges: 1) PoIs are always sparse in the non-location-based social platforms, and it is impractical to measure the similarities of users solely with PoIs; 2) The similarities of hierarchical are hierarchical from the view of word, phrase, and sentence. How to model the hierarchical structure remains a key challenge; 3) The unreliable semantics of words. Two different words may refer to the same physical appearance of users, indicating that users are with the same identities.To tackle the above problems, we propose UGCLink, a knowledge distillation framework that models UGCs to predict user …
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H Gao, Y Wang, J Shao, H Shen, X Cheng - 2021 IEEE International Conference on Big Data (Big …, 2021