TY - A2的刘Zhe-Li盟曾,文静AU - Tang瑞盟——王盟海州,陈Xingshu AU -王,文PY - 2021 DA - 2021/05/26 TI -用户识别基于集成多个用户信息在线社交网络SP - 5533417六世- 2021 AB -用户标识可以帮助我们构建更全面的用户信息。它已经吸引了学术界的重视。大多数现有的作品profile-based用户标识和用户识别特性。由于社交网络用户隐私设置和限制用户数据抓取,用户数据可能丢失或不完整的在真实的社会网络。用户数据包括配置文件、用户生成内容(UGCs),和人际关系。先前的研究可能是稀疏的特征提取。为了减少上述问题对用户身份的影响,我们提出一个多个用户信息的用户识别框架(MUIUI)。首先,我们开发的多进程爬虫获取用户数据从两个流行的社交网站,Twitter和Facebook。其次,我们使用命名实体识别和实体连接获取和整合从概要文件和UGCs地点和组织。我们也从概要文件和UGCs提取url。 We apply the locations jointly with the relationships and develop several algorithms to measure the similarity of the display name, all locations, all organizations, location in profile, all URLs, following organizations, and user ID, respectively. Afterward, we propose a fusion classifier machine learning-based user identification method. The results show that the F1 score of MUIUI reaches 86.46% on the dataset. It proves that MUIUI can reduce the impact of user data that are missing or incomplete. SN - 1939-0114 UR - https://doi.org/10.1155/2021/5533417 DO - 10.1155/2021/5533417 JF - Security and Communication Networks PB - Hindawi KW - ER -