Name
Abstract | ||
|---|---|---|
User identity linkage is to identify all the users belonging to the same individual in different networks and has been widely studied along with the increasing popularity of diverse social media sites. Generally, a pair of probable corresponding users on different networks may form a true “Anchor Link”. Most existing methods identify a user based on unique features (username, interests, friends, etc.) and neglect the importance of users local network structure. Therefore, one challenging problem is how to address the user identity linkage problem if only structural information is available. In this paper, we explore techniques for dealing with the fundamental and accumulated information from neighbouring anchor links. Furthermore, we design a Trustworthy Predicting Approach (TPA) for computing the authority of an anchor link, inferring the trustworthiness of a candidate anchor link being true and predicting whether an anchor link is able to be veritably formed. Experiments illustrate the effectiveness of our proposed algorithm. |
Year | Venue | Field |
|---|---|---|
2018 | WISE | Data mining,Social media,Information retrieval,Trustworthiness,Computer science,Popularity,Neglect,Local area network |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
13 | 5 | |