AsyLink: user identity linkage from text to geo-location via sparse labeled data
文献类型：期刊论文
| 作者 | Shao, Jiangli1,2; Wang, Yongqing2; Gao, Hao1,2; Shi, Boshen1,2; Shen, Huawei2; Cheng, Xueqi2 |
| 刊名 | NEUROCOMPUTING
 |
| 出版日期 | 2023 |
| 卷号 | 515页码:174-184 |
| 关键词 | User identity linkage User -generated text Geo-location |
| ISSN号 | 0925-2312 |
| DOI | 10.1016/j.neucom.2022.10.027 |
| 英文摘要 | User Identity Linkage (UIL) aims to reveal the correspondence among account pairs across different social platforms. It has been a popular but challenging task in recent years as complex application scenarios have emerged. Existing UIL methods mainly formalize a classification problem based on symmetric infor-mation, but these techniques are hard to apply to asymmetric, sparsely labeled, and imbalanced data. To combat the challenges, we propose a novel UIL framework (AsyLink) with asymmetric information in text and geographic forms. AsyLink first uses topic modeling technologies to associate words and locations, where external text-location pairs can be conveniently introduced to reduce bias caused by sparse link-age labels. Then the user-user interactive tensors are constructed as the basis for linking. Using 3D con-volutional neural networks, matching patterns in user-user interactive tensors are captured, and final predictions are based on the extracted features. Meanwhile, instead of regular classification loss, the ranking loss is introduced to predict the best answer among candidates, which is conducive to imbal-anced classification. Experiments performed on four real-world datasets indicate that AsyLink achieves state-of-the-art performances and has great potential for real-world applications. (c) 2022 Elsevier B.V. All rights reserved. |
| 资助项目 | National Natural Science Founda-tion of China ; National Social Science Fund of China ; Beijing Nova Program ; China Postdoctoral Science Foundation ; [U21B2046,61902380] ; [19ZDA329] ; [Z201100006820061] ; [2022M713206] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000877611700010 |
| 出版者 | ELSEVIER |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/20236]  |
| 专题 | 中国科学院计算技术研究所期刊论文 |
| 通讯作者 | Wang, Yongqing |
| 作者单位 | 1.Univ Chinese Acad Sci, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Data Intelligence Syst Res Ctr, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Shao, Jiangli,Wang, Yongqing,Gao, Hao,et al. AsyLink: user identity linkage from text to geo-location via sparse labeled data[J]. NEUROCOMPUTING,2023,515:174-184. |
| APA | Shao, Jiangli,Wang, Yongqing,Gao, Hao,Shi, Boshen,Shen, Huawei,&Cheng, Xueqi.(2023).AsyLink: user identity linkage from text to geo-location via sparse labeled data.NEUROCOMPUTING,515,174-184. |
| MLA | Shao, Jiangli,et al."AsyLink: user identity linkage from text to geo-location via sparse labeled data".NEUROCOMPUTING 515(2023):174-184. |
入库方式： OAI收割
来源：计算技术研究所
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