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Details of Grant 

EPSRC Reference: EP/M012654/1
Title: Justified Assessments of Service Provider Reputation
Principal Investigator: Miles, Dr S
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Black Pepper Software Limited
Department: Informatics
Organisation: Kings College London
Scheme: Standard Research
Starts: 26 January 2015 Ends: 25 July 2018 Value (£): 288,122
EPSRC Research Topic Classifications:
Artificial Intelligence Information & Knowledge Mgmt
EPSRC Industrial Sector Classifications:
Retail Information Technologies
Related Grants:
EP/M012662/1
Panel History:
Panel DatePanel NameOutcome
09 Sep 2014 EPSRC ICT Prioritisation Panel - Sept 2014 Announced
Summary on Grant Application Form
Justified Assessments of Service Provider Reputation (JASPR) aims to improve the way that services are discovered, selected and used by providing rich, personalised reputation assessments of services with the rationale behind those assessments. It is particularly targeted at giving small and medium-sized enterprises (SMEs) better exposure to large clients by reducing clients' reliance on extensive market histories or opaque online reviews that do not account for personalised needs. While large companies can rely on brand influence to bring clients to their services, it is difficult for SMEs to gain market access, especially newer businesses with little history for clients to draw on. This can mean that an SME is overlooked even when providing a service directly matching the client's needs. From the customer side, the project will allow more intelligent service procurement, based on rich reputation assessments reflecting the actual performance of providers, with less bias from branding and superficial reviews.

More generally, in any service-based system, an accurate assessment of reputation is essential for selecting between alternative providers. Existing methods typically assess reputation on a combination of direct experiences by the client being provided with a service and third party recommendations, with the reputation expressed as a numerical score or probability estimate. They do not allow the opportunity to interrogate an assessment to find out why a particular assessment is made, and so whether it is appropriate to a new service selection requirement, and they exclude from consideration a wealth of information about the context of providers' previous actions that could give useful information to a customer in selecting a service provider. For example, there may be mitigating circumstances for past failures, or a provider may have changed their organisational affiliation. These limitations are of particular significance in marketplaces involving both newer and more established service providers. New providers are often disadvantaged in a marketplace since a single negative review can disproportionately harm their reputation, and customers are unable to accurately assess the risk associated with new providers compared to those that are established. To make richer reputation assessments that take into account the context of past service provisions, this context must be modelled and recorded, and can be described as the provenance of the provision.

In the proposed project, we will use provenance records as a source of information on which a more nuanced reputation mechanism can be based. We will define the supporting algorithms and software infrastructure to allow this rich reputation information to be captured, analysed and presented to clients.
Key Findings
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Potential use in non-academic contexts
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