Trust model for social network using singular value decomposition
For effective interactions to take place in a social network, trust is important. We model trust of agents using the peer to peer reputation ratings in the network that forms a real valued matrix. Singular value decomposition discounts the reputation ratings to estimate the trust levels as trust i...
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Interdisciplinary Description of Complex Systems
2019
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author | Ntwiga, Davis Bundi Weke, Patrick Kirumbu, Michael Kiura |
author_facet | Ntwiga, Davis Bundi Weke, Patrick Kirumbu, Michael Kiura |
author_sort | Ntwiga, Davis Bundi |
collection | DSpace |
description | For effective interactions to take place in a social network, trust is important. We model trust of
agents using the peer to peer reputation ratings in the network that forms a real valued matrix.
Singular value decomposition discounts the reputation ratings to estimate the trust levels as trust is the
subjective probability of future expectations based on current reputation ratings.
Reputation and trust are closely related and singular value decomposition can estimate trust using the
real valued matrix of the reputation ratings of the agents in the network.
Singular value decomposition is an ideal technique in error elimination when estimating trust from
reputation ratings. Reputation estimation of trust is optimal at the discounting of 20 %. |
format | Article |
id | oai:repository.daystar.ac.ke:123456789-2964 |
institution | Daystar University |
language | English |
publishDate | 2019 |
publisher | Interdisciplinary Description of Complex Systems |
record_format | dspace |
spelling | oai:repository.daystar.ac.ke:123456789-29642024-02-21T16:41:16Z Trust model for social network using singular value decomposition Ntwiga, Davis Bundi Weke, Patrick Kirumbu, Michael Kiura Discounting Social network Trust Reputation Singular value decomposition For effective interactions to take place in a social network, trust is important. We model trust of agents using the peer to peer reputation ratings in the network that forms a real valued matrix. Singular value decomposition discounts the reputation ratings to estimate the trust levels as trust is the subjective probability of future expectations based on current reputation ratings. Reputation and trust are closely related and singular value decomposition can estimate trust using the real valued matrix of the reputation ratings of the agents in the network. Singular value decomposition is an ideal technique in error elimination when estimating trust from reputation ratings. Reputation estimation of trust is optimal at the discounting of 20 %. 2019-09-04T08:50:58Z 2019-09-04T08:50:58Z 2016-06-01 Article Trust model for social network using singular value decomposition by Kirumbu, Michael Kiura(et..al),Interdisciplinary Description of Complex Systems,2016 https://repository.daystar.ac.ke/handle/123456789/2964 en application/pdf Interdisciplinary Description of Complex Systems |
spellingShingle | Discounting Social network Trust Reputation Singular value decomposition Ntwiga, Davis Bundi Weke, Patrick Kirumbu, Michael Kiura Trust model for social network using singular value decomposition |
title | Trust model for social network using singular value decomposition |
title_full | Trust model for social network using singular value decomposition |
title_fullStr | Trust model for social network using singular value decomposition |
title_full_unstemmed | Trust model for social network using singular value decomposition |
title_short | Trust model for social network using singular value decomposition |
title_sort | trust model for social network using singular value decomposition |
topic | Discounting Social network Trust Reputation Singular value decomposition |
url | https://repository.daystar.ac.ke/handle/123456789/2964 |
work_keys_str_mv | AT ntwigadavisbundi trustmodelforsocialnetworkusingsingularvaluedecomposition AT wekepatrick trustmodelforsocialnetworkusingsingularvaluedecomposition AT kirumbumichaelkiura trustmodelforsocialnetworkusingsingularvaluedecomposition |