Method and device for mining cheating user

Abstract

The invention discloses a method and device for mining cheating users. The method comprises the following steps of: obtaining representation information of all users; calculating user cheating scores corresponding to the representation information of all the users according to preset scoring strategies; and determining users with user cheating scores which exceed a preset cheating score threshold as the cheating users. By using the method and the device for mining cheating users, the cheating users can be effectively recognized and the anti-cheating efficiency of communities is improved.

Description

technical field [0001] The invention relates to computer communication technology, in particular to a method and device for mining cheating users. Background technique [0002] With the development of computer communication technology, especially the development of 3G network and intelligent mobile terminals, users' network life is becoming more and more abundant, such as chatting, browsing news, watching movies, playing games, searching, shopping, and publishing information on the Internet. It has increasingly become a part of online life. For example, users can exchange and share information and obtain corresponding points by logging in to the community, posting information or replying to questions raised by other users. Among them, a community refers to a social network structure system composed of individuals or organizations, and the people or organizations in the social network structure system are connected through one or more relationships, including but not limited ...

AI Technical Summary

Problems solved by technology

[0009] As can be seen from the above, the existing anti-cheating methods determine whether the webpage is a cheating webpage by analyzing the content of the webpage, and filter or delete the webpages determined to be cheating, but fail to effectively identify the cheating user who created the cheating webpage. The cheating user can continue to cheat by creating other cheating webpages, which makes the probability of user cheating higher and the efficiency of anti-cheating lower; furthermore, since there are generally few data links (anchor text links) in community webpages, it is easy to distinguish through formulas Leaving out cheating web pages with few anchor text links, and the user level is uneven, and the cost of creating cheating data is low. For example, it is easy to use a popular keyword to cheat in a log. There are endless cheating methods. It is difficult to effectively detect cheating users with links and hidden content on web pages, and the efficiency of anti-cheating is not high

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