Trust Management for the Semantic Web

By Matthew Richardson, Rakesh Agrawal, Pedro M. Domingos. International Workshop on the Semantic Web, 2003

513 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/b242449cfb6f681ad3c6cfd66afece3ba03bf35d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Information Systems

In Sociology and Political Science

Citations in the corpus

SybilLimit: A Near-Optimal Social Network Defense Against Sybil Attacks (2010, background): “Unlike many other works [8, 13, 32, 36] on trust networks, SybilLimit does not use trust propagation in the social network.”
TrustGuard: countering vulnerabilities in reputation management for decentralized overlay networks (2005, background): “[17] developed a path-algebra model for trust propagation.”
Spreading activation models for trust propagation (2004, background): “The malady that Appleseed suffers from is common to many trust metrics, most notably those based upon finding principal eigenvectors [29, 17, 33].”
SoK: The Evolution of Sybil Defense via Social Networks (2013, methodology): “This ranking is significantly more robust than that obtained by methods based on PageRank (see for example EigenTrust [28], TrustRank [47]) or that apply PPR directly [21].”
A Survey of Signed Network Mining in Social Media (2015, methodology): “gorithms of unsigned networks, such as EigenTrust [Kamvar et al. 2003], by ignoring negative links or zero the entries corresponding to the negative links in the matrix representation of the network [Richardson et al. 2003]. In other words, we only consider the positive network Ap whileignoringtheim”
Scalable modeling of real graphs using Kronecker multiplication (2007, background): “Last, we present the results of ﬁtting Epinions graph.”
Controlling edge dynamics in complex networks (2011, unknown): “N-EC-2 418 519 [37] A regulates B 3. TRN-Yeast-1 4,441 12,873 [7] A regulates B 4. TRN-Yeast-2 688 1,079 [37] A regulates B Trust 5. College 32 96 [36,61] A is trusted by B 6. Epinions 75,888 508,837 [55] A is trusted by B 7. Prison 67 182 [36,61] A is trusted by B 8. Slashdot 82,168 948,464 [30] A ”
Named graphs, provenance and trust (2005, background): “Most trust architectures proposed for the Semantic Web so far fall into this category [12, 1, 7].”