Exploring Different Types of Trust Propagation

Jøsang, Audun; Marsh, Stephen; Pope, Simon

doi:10.1007/11755593_14

Cited by 115 publications

(114 citation statements)

References 9 publications

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“…we obtain Equation (16). In fact, we consider each item of − → P as providing an observation about s.…”

Section: Partial Evidence Observationmentioning

confidence: 99%

“…More often, we use Equation 16, because we consider the cases where evidence from different and independent facts about the same individual are provided.…”

Section: Partial Evidence Observationmentioning

confidence: 99%

“…Subjective logic's operators allow combining opinions in different manners, and their development has been widely investigated. Remarkably, the averaging and cumulative fusion [13,14] (i.e., operators that allow averaging or cumulating opinions about the same proposition from different sources) and the discounting [16] (i.e., the operator that allows weighing a source's opinion based on the source's reputation) operators are among the most generic and useful operators for this logic. These operators provide the foundations for the work proposed in this chapter.…”

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

Bridging Gaps Between Subjective Logic and Semantic Web

Ceolin¹,

Nottamkandath²,

Fokkink³

2014

Uncertainty Reasoning for the Semantic Web III

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Abstract. Subjective logic is a powerful probabilistic logic which is useful to handle data in case of uncertainty. Subjective logic and the Semantic Web can mutually benefit from each other, since subjective logic is useful to handle the inner noisiness of the Semantic Web data, while the Semantic Web offers a means to obtain evidence useful for performing evidential reasoning based on subjective logic. In this chapter we describe three extensions and applications of subjective logic in the Semantic Web, namely: the use of deterministic and probabilistic semantic similarity measures for weighing subjective opinions, a way for accounting for partial observations, and "open world opinion", i.e. subjective opinions based on Dirichlet processes, which extend multinomial opinions. For each of these extensions, we provide examples and applications to prove their validity.

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“…we obtain Equation (16). In fact, we consider each item of − → P as providing an observation about s.…”

Section: Partial Evidence Observationmentioning

confidence: 99%

“…More often, we use Equation 16, because we consider the cases where evidence from different and independent facts about the same individual are provided.…”

Section: Partial Evidence Observationmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Bridging Gaps Between Subjective Logic and Semantic Web

Ceolin¹,

Nottamkandath²,

Fokkink³

2014

Uncertainty Reasoning for the Semantic Web III

View full text Add to dashboard Cite

show abstract

“…Reputation systems have to face the problem of statistically dependent recommendations (Jøsang et al, 2006;Ramchurn et al, 2004). This is especially necessary in decentralised systems.…”

Section: Evaluation Of the Local Reputationmentioning

confidence: 99%

“…So, the more the car M trusts the car B regarding the given information type, the more weight B's opinion gains in the fusion process. This is done by the base rate sensitive discounting as discussed in Jøsang et al (2006). This operation weights the opinion of trustworthy cars higher in the subsequent opinion fusion.…”

Section: Evaluation Of the Local Reputationmentioning

confidence: 99%

Ability-aware trust for vehicular networks

Bamberger

Schlittenlacher

Diepold

2012

IJSCCPS

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Future vehicles will exchange much information through a wireless network in order to efficiently maintain their inner model of the environment. Before they can believe received pieces of information, they must evaluate their reliability. Trust is a mechanism to estimate this reliability based on the sender. It depends on friendship-like relations between vehicles, the social structure.Our traffic and network simulation shows that such relations indeed arise, because vehicles often drive the same route. Within this simulation, all vehicles are equipped with the proposed trust model, which continuously monitors the experiences made with others. The model focuses on these direct experiences of the individual and does not depend on a central reputation unit. It continuously evaluates the performance and reputation of other vehicles and includes a feedback loop to faster adapt to changes in the other's behaviour. Since the performance of a vehicle depends on the abilities of its sensors, like different abilities in velocity measurement or in traffic sign detection, the proposed model develops trust depending on the sender and on the type of the information.

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Fuzzy Computational Models of Trust and Distrust for Enhanced Recommendations

Kant

Bharadwaj

2013

Int. J. Intell. Syst.

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Trust models have received considerable attention in the recent past and have been employed in many of today's most successful recommender systems (RSs) for alleviating sparsity by enhancing their interuser connectivity obtained from historical preference data and to address the cold start problem. However, the incorporation of distrust in addition to trust for improved recommendations has not been analyzed fully because of the absence of publically available data sets containing gradual information about trust and distrust concepts. Our work in this paper is an attempt toward introducing recommendation strategies exploiting both the trust and the distrust in the RSs to further enhance their quality of recommendations through fuzzy computational models for trust and distrust. Since trust and distrust concepts are gradual phenomenon, therefore these can be represented more naturally by fuzzy logic using linguistic expressions. The contributions of this paper are three fold: First, we propose fuzzy computational models for both the trust and distrust concepts through similarity as well as knowledge factors based on linguistic expressions. Second, we suggest appropriate propagation and aggregation operators to deal with the data sparsity. Finally, we present a comparative analysis of proposed recommendation strategies utilizing both the trust and distrust concepts.

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Exploring Different Types of Trust Propagation

Cited by 115 publications

References 9 publications

Bridging Gaps Between Subjective Logic and Semantic Web

Bridging Gaps Between Subjective Logic and Semantic Web

Ability-aware trust for vehicular networks

Fuzzy Computational Models of Trust and Distrust for Enhanced Recommendations

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