Learning to Correlate Accounts Across Online Social Networks: An Embedding-Based Approach

Volume: 32, Issue: 3, Pages: 714 - 729
Published: Jul 1, 2020
Abstract
Cross-site account correlation correlates users who have multiple accounts but the same identity across online social networks (OSNs). Being able to identify cross-site users is important for a variety of applications in social networks, security, and electronic commerce, such as social link prediction and cross-domain recommendation. Because of either heterogeneous characteristics of platforms or some unobserved but intrinsic individual...
Paper Details
Title
Learning to Correlate Accounts Across Online Social Networks: An Embedding-Based Approach
Published Date
Jul 1, 2020
Volume
32
Issue
3
Pages
714 - 729
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