caa a22 4500 606229116 CHVBK 20210128101207.0 cr unu---uuuuu 210128e20150801xx s 000 0 eng 10.1007/s10796-014-9522-5 doi (NATIONALLICENCE)springer-10.1007/s10796-014-9522-5 Subjective logic operators in trust assessment: an empirical study [Elektronische Daten] [Federico Cerutti, Lance Kaplan, Timothy Norman, Nir Oren, Alice Toniolo] Computational trust mechanisms aim to produce trust ratings from both direct and indirect information about agents' behaviour. Subjective Logic (SL) has been widely adopted as the core of such systems via its fusion and discount operators. In recent research we revisited the semantics of these operators to explore an alternative, geometric interpretation. In this paper we present principled desiderata for discounting and fusion operators in SL. Building upon this we present operators that satisfy these desirable properties, including a family of discount operators. We then show, through a rigorous empirical study, that specific, geometrically interpreted, operators significantly outperform standard SL operators in estimating ground truth. These novel operators offer real advantages for computational models of trust and reputation, in which they may be employed without modifying other aspects of an existing system. Springer Science+Business Media New York, 2014 Trust and reputation nationallicence Information fusion nationallicence Uncertain reasoning nationallicence Cerutti Federico School of Natural and Computing Science King's College, University of Aberdeen, AB24 3UE, Aberdeen, UK aut Kaplan Lance US Army Research Laboratory, Adelphi, MD, USA aut Norman Timothy School of Natural and Computing Science King's College, University of Aberdeen, AB24 3UE, Aberdeen, UK aut Oren Nir School of Natural and Computing Science King's College, University of Aberdeen, AB24 3UE, Aberdeen, UK aut Toniolo Alice School of Natural and Computing Science King's College, University of Aberdeen, AB24 3UE, Aberdeen, UK aut Information Systems Frontiers Springer US; http://www.springer-ny.com 17/4(2015-08-01), 743-762 1387-3326 17:4<743 2015 17 10796 https://doi.org/10.1007/s10796-014-9522-5 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10796-014-9522-5 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Cerutti Federico School of Natural and Computing Science King's College, University of Aberdeen, AB24 3UE, Aberdeen, UK aut NATIONALLICENCE 700 1- Kaplan Lance US Army Research Laboratory, Adelphi, MD, USA aut NATIONALLICENCE 700 1- Norman Timothy School of Natural and Computing Science King's College, University of Aberdeen, AB24 3UE, Aberdeen, UK aut NATIONALLICENCE 700 1- Oren Nir School of Natural and Computing Science King's College, University of Aberdeen, AB24 3UE, Aberdeen, UK aut NATIONALLICENCE 700 1- Toniolo Alice School of Natural and Computing Science King's College, University of Aberdeen, AB24 3UE, Aberdeen, UK aut NATIONALLICENCE 773 0- Information Systems Frontiers Springer US; http://www.springer-ny.com 17/4(2015-08-01), 743-762 1387-3326 17:4<743 2015 17 10796