Abstract
Because users usually use multiple network applications, there are many duplicate user identities in the Internet. The integration and determination of these duplicate identities are of great significance in the field of commerce and network security. For privacy and security considerations, the username is easy to obtain and does not involve the privacy, and can reflect the user's habits and individuality. Therefore, this paper presents a method of discriminating user's identity similarity based on username feature greedy matching. Firstly, the description of user's identity similarity is divided into username feature description and feature string similarity description, and the optimal feature weights and similarity thresholds are obtained according to the training set with the known corresponding relation. An experiment in the dataset and draw potential username pairs for the same user.
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