Novel Method of Edge-Removing Walk for Graph Representation in User Identity Linkage
Random-walk-based graph representation methods have been widely applied in User Identity Linkage (UIL) tasks, which links overlapping users between two different social networks. It can help us to obtain more comprehensive portraits of criminals, which is helpful for improving cyberspace governance....
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-02-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/13/4/715 |
| _version_ | 1797298413548601344 |
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| author | Xiaqing Xie Wenyu Zang Yanlin Hu Jiangyu Ji Zhihao Xiong |
| author_facet | Xiaqing Xie Wenyu Zang Yanlin Hu Jiangyu Ji Zhihao Xiong |
| author_sort | Xiaqing Xie |
| collection | DOAJ |
| description | Random-walk-based graph representation methods have been widely applied in User Identity Linkage (UIL) tasks, which links overlapping users between two different social networks. It can help us to obtain more comprehensive portraits of criminals, which is helpful for improving cyberspace governance. Yet, random walk generates a large number of repeating sequences, causing unnecessary computation and storage overhead. This paper proposes a novel method called Edge-Removing Walk (ERW) that can replace random walk in random-walk-based models. It removes edges once they are walked in a walk round to capture the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>l</mi><mo>−</mo><mi>h</mi><mi>o</mi><mi>p</mi></mrow></semantics></math></inline-formula> features without repetition, and it walks the whole graph for several rounds to capture the different kinds of paths starting from a specific node. Experiments proved that ERW can exponentially improve the efficiency for random-walk-based UIL models, even maintaining better performance. We finally generalize ERW into a general User Identity Linkage framework called ERW-UIL and verify its performance. |
| first_indexed | 2024-03-07T22:34:30Z |
| format | Article |
| id | doaj.art-63dd17364f474d51a02a2bf98c15e09e |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-07T22:34:30Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-63dd17364f474d51a02a2bf98c15e09e2024-02-23T15:14:44ZengMDPI AGElectronics2079-92922024-02-0113471510.3390/electronics13040715Novel Method of Edge-Removing Walk for Graph Representation in User Identity LinkageXiaqing Xie0Wenyu Zang1Yanlin Hu2Jiangyu Ji3Zhihao Xiong4Key Laboratory of Trustworthy Distributed Computing and Service (BUPT), Ministry of Education, Beijing 100876, ChinaAcademy of Cyber, China Electronics Technology Group Corporation, Beijing 100085, ChinaNational Computer Network Emergency Response Technical Team, Coordination Center of China (CNCERT/CC), Beijing 100029, ChinaKey Laboratory of Trustworthy Distributed Computing and Service (BUPT), Ministry of Education, Beijing 100876, ChinaKey Laboratory of Trustworthy Distributed Computing and Service (BUPT), Ministry of Education, Beijing 100876, ChinaRandom-walk-based graph representation methods have been widely applied in User Identity Linkage (UIL) tasks, which links overlapping users between two different social networks. It can help us to obtain more comprehensive portraits of criminals, which is helpful for improving cyberspace governance. Yet, random walk generates a large number of repeating sequences, causing unnecessary computation and storage overhead. This paper proposes a novel method called Edge-Removing Walk (ERW) that can replace random walk in random-walk-based models. It removes edges once they are walked in a walk round to capture the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>l</mi><mo>−</mo><mi>h</mi><mi>o</mi><mi>p</mi></mrow></semantics></math></inline-formula> features without repetition, and it walks the whole graph for several rounds to capture the different kinds of paths starting from a specific node. Experiments proved that ERW can exponentially improve the efficiency for random-walk-based UIL models, even maintaining better performance. We finally generalize ERW into a general User Identity Linkage framework called ERW-UIL and verify its performance.https://www.mdpi.com/2079-9292/13/4/715network embeddingUser Identity Linkageuser alignment |
| spellingShingle | Xiaqing Xie Wenyu Zang Yanlin Hu Jiangyu Ji Zhihao Xiong Novel Method of Edge-Removing Walk for Graph Representation in User Identity Linkage Electronics network embedding User Identity Linkage user alignment |
| title | Novel Method of Edge-Removing Walk for Graph Representation in User Identity Linkage |
| title_full | Novel Method of Edge-Removing Walk for Graph Representation in User Identity Linkage |
| title_fullStr | Novel Method of Edge-Removing Walk for Graph Representation in User Identity Linkage |
| title_full_unstemmed | Novel Method of Edge-Removing Walk for Graph Representation in User Identity Linkage |
| title_short | Novel Method of Edge-Removing Walk for Graph Representation in User Identity Linkage |
| title_sort | novel method of edge removing walk for graph representation in user identity linkage |
| topic | network embedding User Identity Linkage user alignment |
| url | https://www.mdpi.com/2079-9292/13/4/715 |
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