Features and Connection Based Network Alignment Method - Mungen, Ahmet Anil; Kaya, Mehmet (Ieee, 2019)
In almost all proposed computer science algorithms, success rates are directly related to the data set. Recommendation and link prediction methods are the most critical methods in which the success of the repository directly affects the success of the method. The cold-start problem can be classified as basically a missing data problem. Since there are dozens of social networks in the world, not being able to collect all data in one source can be called as missing data problem. The fact that the users' Twitter pages cannot be used as a single source without other social networks like Instagram for collecting data about users. Instead of this, it can be more successful if data from both networks to connect. It is not usual for users to link accounts across different social networks or merge them into a single account. This study aimed to find the same users in different social networks by looking at the attributes of the profile, their connections, and shares on the network. In this study, based on the status and shares of the users on the network, the proposed method has been successfully found in the profiles of the person in different networks.
International Conference on Artificial Intelligence and Data Processing (IDAP) -- SEP 21-22, 2019 -- Inonu Univ, Malatya, TURKEY
Keywords: node alignment; finding profiles of different people