Abstract
Discounting and fusing trust is a fundamental work in trust inference. Existing trust discounting operators are mainly based on the structure balance theory but ignoring the distribution of the balanced triads, and the trust fusion operator for dependent opinions is also not practical. In order to solve these issues, we propose an adaptive trust discounting operator based on the structure balance theory taking into account the distribution regularities of the balanced transitive triads. An partial dependent trust fusion operator is also given to deal with recommenders’ conflicting judgements on the same observations. Comparative experiments show that the proposed trust discounting and fusion operators can yield better trust inference accuracy than existing ones.
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Ma, Y., Lu, H., Gan, Z., Ma, X. (2014). Trust Discounting and Trust Fusion in Online Social Networks. In: Chen, L., Jia, Y., Sellis, T., Liu, G. (eds) Web Technologies and Applications. APWeb 2014. Lecture Notes in Computer Science, vol 8709. Springer, Cham. https://doi.org/10.1007/978-3-319-11116-2_59
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DOI: https://doi.org/10.1007/978-3-319-11116-2_59
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11115-5
Online ISBN: 978-3-319-11116-2
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