Abstract
Computational trust in the social media depends both on the interaction types and on the expertise, which exposes user’s interests by tags on items such as books, articles, images etc. However, when there is not any interaction among users, such a computation is impossible. In this paper, we first propose a novel model of computational trust among users in social network to incorporate the interaction among users and semantics of topics based on tags posted by users. Both types of direct and indirect interaction via intermediate ones are utilized for computation in the model. Then, we introduce algorithms for computing trust among users in social network.
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Pham, P.T., Nguyen, M.H., Tran, D.Q. (2017). Incorporation of Experience and Reference-Based Topic Trust with Interests in Social Network. In: Akagi, M., Nguyen, TT., Vu, DT., Phung, TN., Huynh, VN. (eds) Advances in Information and Communication Technology. ICTA 2016. Advances in Intelligent Systems and Computing, vol 538. Springer, Cham. https://doi.org/10.1007/978-3-319-49073-1_31
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DOI: https://doi.org/10.1007/978-3-319-49073-1_31
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