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Propagating and Aggregating Trust with Uncertainty Measure

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Computational Collective Intelligence. Technologies and Applications (ICCCI 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6922))

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Abstract

Trust networks have been recognized as a valuable component of many modern systems, such as e-commerce or recommender systems, as they provide a way of quality assessment.

In addition to adequate modeling of trust in such network, two fundamental issues need to be addressed: the methods of propagation and aggregation of trust.

In this paper we present an operator that performs both propagation and aggregation of trust. Trust is modeled on the basis of IFS theory (Atanassov’s intuitionistic fuzzy set theory) with particular emphasis on uncertainty, and the operator is based on relative scalar cardinality of IFS. The operator can be used in a very flexible manner for prediction of local and global trust.

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Stachowiak, A. (2011). Propagating and Aggregating Trust with Uncertainty Measure. In: Jędrzejowicz, P., Nguyen, N.T., Hoang, K. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2011. Lecture Notes in Computer Science(), vol 6922. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23935-9_28

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  • DOI: https://doi.org/10.1007/978-3-642-23935-9_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23934-2

  • Online ISBN: 978-3-642-23935-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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