Strategies for incorporating knowledge defects and path length in trust aggregation
- Author
- Nele Verbiest (UGent) , Chris Cornelis (UGent) , Patricia Victor (UGent) and Enrique Herrera-Viedma
- Organization
- Abstract
- The ability for a user to accurately estimate the amount of trust to be placed in a peer user is gaining more and more attention in social network applications. Trust aggregation provides this ability by identifying paths that connect users in the network, and by merging trust opinions expressed by users along these paths. However, as individual trust opinions are not always based on perfect knowledge, and since the quality of a trust estimation propagated along a given path may diminish as its length increases, mechanisms are needed to handle these imperfections. In this paper, we propose a set of trust aggregation operators that take into account; knowledge defects and path length. We investigate their properties, and discuss how they may be implemented in practice, taking into account; characteristics of the network such as the availability of a central authority, or the need to preserve users' privacy by not publically disclosing their trust information.
- Keywords
- OPERATORS
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-1079632
- MLA
- Verbiest, Nele, et al. “Strategies for Incorporating Knowledge Defects and Path Length in Trust Aggregation.” LECTURE NOTES IN ARTIFICIAL INTELLIGENCE, edited by Nicolás García Pedrajas et al., vol. 6098, Springer, 2010, pp. 450–59, doi:10.1007/978-3-642-13033-5_46.
- APA
- Verbiest, N., Cornelis, C., Victor, P., & Herrera-Viedma, E. (2010). Strategies for incorporating knowledge defects and path length in trust aggregation. In N. García Pedrajas, F. Herrera, C. Fyfe, J. M. Benítez, & M. Ali (Eds.), LECTURE NOTES IN ARTIFICIAL INTELLIGENCE (Vol. 6098, pp. 450–459). https://doi.org/10.1007/978-3-642-13033-5_46
- Chicago author-date
- Verbiest, Nele, Chris Cornelis, Patricia Victor, and Enrique Herrera-Viedma. 2010. “Strategies for Incorporating Knowledge Defects and Path Length in Trust Aggregation.” In LECTURE NOTES IN ARTIFICIAL INTELLIGENCE, edited by Nicolás García Pedrajas, Francisco Herrera, Colin Fyfe, José Manuel Benítez, and Moonis Ali, 6098:450–59. Berlin, Germany: Springer. https://doi.org/10.1007/978-3-642-13033-5_46.
- Chicago author-date (all authors)
- Verbiest, Nele, Chris Cornelis, Patricia Victor, and Enrique Herrera-Viedma. 2010. “Strategies for Incorporating Knowledge Defects and Path Length in Trust Aggregation.” In LECTURE NOTES IN ARTIFICIAL INTELLIGENCE, ed by. Nicolás García Pedrajas, Francisco Herrera, Colin Fyfe, José Manuel Benítez, and Moonis Ali, 6098:450–459. Berlin, Germany: Springer. doi:10.1007/978-3-642-13033-5_46.
- Vancouver
- 1.Verbiest N, Cornelis C, Victor P, Herrera-Viedma E. Strategies for incorporating knowledge defects and path length in trust aggregation. In: García Pedrajas N, Herrera F, Fyfe C, Benítez JM, Ali M, editors. LECTURE NOTES IN ARTIFICIAL INTELLIGENCE. Berlin, Germany: Springer; 2010. p. 450–9.
- IEEE
- [1]N. Verbiest, C. Cornelis, P. Victor, and E. Herrera-Viedma, “Strategies for incorporating knowledge defects and path length in trust aggregation,” in LECTURE NOTES IN ARTIFICIAL INTELLIGENCE, Cordoba, Spain, 2010, vol. 6098, pp. 450–459.
@inproceedings{1079632,
abstract = {{The ability for a user to accurately estimate the amount of trust to be placed in a peer user is gaining more and more attention in social network applications. Trust aggregation provides this ability by identifying paths that connect users in the network, and by merging trust opinions expressed by users along these paths. However, as individual trust opinions are not always based on perfect knowledge, and since the quality of a trust estimation propagated along a given path may diminish as its length increases, mechanisms are needed to handle these imperfections. In this paper, we propose a set of trust aggregation operators that take into account; knowledge defects and path length. We investigate their properties, and discuss how they may be implemented in practice, taking into account; characteristics of the network such as the availability of a central authority, or the need to preserve users' privacy by not publically disclosing their trust information.}},
author = {{Verbiest, Nele and Cornelis, Chris and Victor, Patricia and Herrera-Viedma, Enrique}},
booktitle = {{LECTURE NOTES IN ARTIFICIAL INTELLIGENCE}},
editor = {{García Pedrajas, Nicolás and Herrera, Francisco and Fyfe, Colin and Benítez, José Manuel and Ali, Moonis}},
isbn = {{9783642130328}},
issn = {{0302-9743}},
keywords = {{OPERATORS}},
language = {{eng}},
location = {{Cordoba, Spain}},
pages = {{450--459}},
publisher = {{Springer}},
title = {{Strategies for incorporating knowledge defects and path length in trust aggregation}},
url = {{http://doi.org/10.1007/978-3-642-13033-5_46}},
volume = {{6098}},
year = {{2010}},
}
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