Trust modeling in social tagging of multimedia content

Abstract

Social networks are very popular now days, as it facilitates search and retrieval of multimedia features. Anyway, noisy and spam annotations often make it difficult to perform an efficient search. Users may make mistakes in tagging and irrelevant tags and content may be maliciously added for advertisement or self-promotion. This article examine recent advances in techniques for combating such noise and spam in social tagging. The trust relationship among users has a direct impact on the sharing and transmission mode of digital contents. To effectively assess direct or recommended trust between users, this paper proposed a
multimedia social networks trust model based on small world theory. Online and Internet databases and early websites
deployed them as a way for publishers to help users find
content.