Spreading activation models for trust propagation

By Cai-Nicolas Ziegler, Georg Lausen. IEEE International Conference on e-Technology, e-Commerce and e-Service, 2004. EEE '04. 2004, 2004

353 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/6418a450da208d608b4eec3730d17ca3c3294b93

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Citations in the corpus

A survey of trust and reputation systems for online service provision (2007, methodology): “5, the Appleseed algorithm [73] and Advogato’s reputation scheme [38] described in Sec.”
Trust-Aware Collaborative Filtering for Recommender Systems (2004, background): “Trust metrics [3,14,8] have precisely the goal of predicting, given a certain user, trust in unknown users based on the complete trust network.”
Inferring binary trust relationships in Web-based social networks (2006, background): “One problem that arises in algorithms that are based on finding the principal eigenvector, like Kamvar [2003], Zeigler and Lausen [2004], and Richardson et al. [2003], is that trust must first be normalized to work within the matrix.”
Recommender Systems (2016, neutral): “A variety of other trust propagation methods include the use of decay factors along paths [240], using only shortest paths [222], distance from a fixed propagation horizon [403], spreading factors [682, 683], rules [345, 597], and semantic distances [1].”
Investigating interactions of trust and interest similarity (2007, methodology): “However, we believe that local group trust metrics like Levien's Advogato [34] and Appleseed [61,62] best fit neighborhood formation in decentralized systems [59].”
Alleviating the Sparsity Problem of Collaborative Filtering Using Trust Inferences (2005, methodology): “We adopt a transitivity rule that facilitates the computation of the confidence between a source user and a target user through a trust path [21, 22].”
Controversial Users Demand Local Trust Metrics: An Experimental Study on Epinions.com Community (2005, methodology): “Trust Metrics (Golbeck, Hendler, & Parsia 2003; Levien 2003; Ziegler & Lausen 2004; Massa & Avesani 2004) are a technique used to predict trust scores of users.”
Computing and Applying Trust in Web-based Social Networks (2005, background): “Ziegler and Lausen(2004a) also introduce a mechanism for using trust to calculate recommendations.”
Recommender Systems (2012, background): “When trust relations between the users are weighted (with trust values 1 and 0 representing total trust and distrust, respectively), the plain trust propagation can be shown to be insufficient—the Appleseed algorithm solves this problem by creating virtual trust edges for backward propagation [248].”