中圖分類號(hào)：TP39 文獻(xiàn)標(biāo)志碼：A DOI: 10.16157/j.issn.0258-7998.245904
中文引用格式： 臧文羽，頡夏青，邱莉榕，等. 基于多頭注意力的社交網(wǎng)絡(luò)用戶身份鏈接方法[J]. 電子技術(shù)應(yīng)用，2024，50(12)：61-64.
英文引用格式： Zang Wenyu，Xie Xiaqing，Qiu Lirong，et al. Social network user identity linkage method based on multi-head attention[J]. Application of Electronic Technique，2024，50(12)：61-64.

Social network user identity linkage method based on multi-head attention

Abstract： With the rapid development of social networks, people have various virtual identities in social networks. User identity linkage problem that aims to identify various virtual identities of the same natural person is becoming increasingly important. User identity linkage method can unearth some hidden information and form a complete user profile to promote the development of multiple research fields, such as cross-network recommendation, link prediction, information dissemination, etc. Existing user-profile based model and network-structure based user identity linkage model do not consider the influence difference between different users, and the convergence speed is slow. In order to model the influences between users, multi-head attention mechanism is added to network random-walk based user linkage method in this paper. The experimental results show that it can improve the effectiveness of social network user identity linkage method and improve training efficiency.

Key words : graph embedding；user identity linkage；multi-head attention mechanism