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Agent-Based Service Selection

29 Pages Posted: 23 Jun 2018 Publication Status: Accepted

See all articles by Raghuram Sreenath

Raghuram Sreenath

IBM - Research Triangle Park

Munindar Singh

North Carolina State University - Department of Computer Science

Abstract

This paper formulates the problem of service selection. It reformulates two traditional recommended approaches for service selection and proposes a new agent-based approach in which agents cooperate to evaluate service providers. In this approach, the agents rate each other, and autonomously decide how much to weigh each other's recommendations. The underlying algorithm with which the agents reason is developed in the context of a concept lattice, which enables finding relevant agents. Since large service selection datasets do not yet exist, for the purposes of evaluation, we reformulate the well-known product evaluations dataset MovieLens as a services dataset. We use it to compare the various approaches. Despite limiting the ow of information, the proposed approach compares well with the existing approaches in terms of some accuracy metrics defined within.

Keywords: service selection, agents, recommendation and rating systems

Suggested Citation

Sreenath, Raghuram and Singh, Munindar, Agent-Based Service Selection (2004). Available at SSRN: https://ssrn.com/abstract=3199021 or http://dx.doi.org/10.2139/ssrn.3199021

Raghuram Sreenath

IBM - Research Triangle Park

3039 Cornwallis Road
Research Triangle Park, NC 27709
United States

Munindar Singh

North Carolina State University - Department of Computer Science

Campus Box 8206, 890 Oval Drive
Engineering Building II
Raleigh, NC 27695
United States

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