Works (5)

Updated: July 5th, 2023 15:47

2013 journal article

Shin: Generalized Trust Propagation with Limited Evidence

COMPUTER, 46(3), 78–85.

By: C. Hang n, Z. Zhang n & M. Singh n

Contributors: C. Hang n, Z. Zhang n & M. Singh n

TL;DR: Shin incorporates a probabilistic method for revising trust estimates in trustees, yielding higher prediction accuracy than traditional approaches that base trust exclusively on a series of referrals culminating with the trustee. (via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: August 6, 2018

2012 journal article

Generalized framework for personalized recommendations in agent networks

AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS, 25(3), 475–498.

By: C. Hang n & M. Singh n

Contributors: C. Hang n & M. Singh n

author keywords: Agent mining; Personalized recommendation; Social networks; Ratings networks; Trust
TL;DR: A new recommendation approach is proposed, dubbed LocPat, which can recommend trustworthy agents to a requester in an agent network based on similarity scores that reflect both the link structure and the trust values on the edges. (via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: August 6, 2018

2011 journal article

A Probabilistic Approach for Maintaining Trust Based on Evidence

JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, 40, 221–267.

By: Y. Wang, C. Hang* & M. Singh*

Contributors: Y. Wang, C. Hang* & M. Singh*

TL;DR: This paper builds on a formal model that considers probability and certainty as two dimensions of trust and proposes a mechanism using which an agent can update the amount of trust it places in other agents on an ongoing basis. (via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: August 6, 2018

2011 journal article

Trustworthy Service Selection and Composition

ACM Transactions on Autonomous and Adaptive Systems, 6(1), 1–17.

By: C. Hang n & M. Singh n

Contributors: C. Hang n & M. Singh n

author keywords: Algorithms; Experimentation; Trust; probabilistic modeling; service-oriented computing
TL;DR: This work proposes two distributed trust-aware service selection approaches: one based on Bayesian networks and the other on a beta-mixture model and shows that both approaches accurately punish and reward services in terms of the qualities they offer, and further that the approaches are effective despite incomplete observations regarding the services under consideration. (via Semantic Scholar)
Sources: Web Of Science, ORCID, Crossref
Added: August 6, 2018

2010 conference paper

From quality to utility: Adaptive service selection framework

Service-oriented computing, 6470, 456–470.

By: C. Hang & M. Singh

Source: NC State University Libraries
Added: August 6, 2018

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