| Accompanying with the development of the global economy and science and technologyprogress, the Online Social Network are stepping into our daily lives. The social networkingservices do not only provide a exchange platform for all users, but also give a chance to sharediaries, photos, emotion, music, and make friends for all users. The more demand for OnlineSocial Network, the more cognition for using Online Social Network. Because of theInternet’s dynamics, openness, and can be shared, it brings new changes and convenience toour lives; but, in addition, the users’ credit problems arrive.Artificial Immune Algorithm has a advanced ability of optimization overall, because itsinhibit similar antibodies as well as to maintain diversity, and cones to be an important toolfor optimizing complicated function. Currently, the most widely used theory is “IdiotypicNetworks” which addressed by Jerne in1974. After this, most of theories of immune networkare on the basis of Jerne’s.In this paper, the problem of trust on Online Social Network for some exploration andresearch, and added Artificial Immune Algorithm proposed building an trust model in OnlineSocial Network based on Artificial Immune Algorithm, which is a major innovation of thispaper point. This article draws on Artificial Immune Algorithm calculated affinity, antigen andantibody clone selection and suppression characteristics, added to the calculation of thedegree of trust in the online social network, to find the purpose of the user by calculating thetrust neighbors, as the purpose of the user’s trusted users. Specific calculated based onArtificial Immune Algorithm trust in online social networks.Artificial Immune Algorithm hasa better and more objective judgment, and improves advantages for online social networks.Through experimental analysis, this former is more accuracy and objectivity intuitively;furthermore it proves the superiority of building trust model by Artificial Immune Algorithmduring online social networks. |
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