DSpam: Defending Against Spam in Tagging Systems via Users´ Reliability

Resisting spam in tagging system is very challenging. This paper presents DSpam, a novel spam-resistant tagging system which can significantly diminish spam in tag search results with users´ reliabilities. DSpam client groups other users into unfamiliar users and interacted users according to the fact whether the client has interacted with such users. For an unfamiliar user, the client computes his reliability by tagging behavior-based mechanism which reflects correlation of annotations between them. For an interacted user, the reliability includes two parts: feedback-based reliability, which indicates direct interactions between that user and the client, and recommendation reliability, which indicates the evaluation about that user from the client´s friends. The client ranks search result with the average reliabilities of himself with respect to annotators of each result. Experimental results show DSpam can effectively resist tag spam and work better than existing tag search schemes.