English

Reputation Bootstrapping for Composite Services using CP-nets

Artificial Intelligence 2021-06-01 v1

Abstract

We propose a novel framework to bootstrap the reputation of on-demand service compositions. On-demand compositions are usually context-aware and have little or no direct consumer feedback. The reputation bootstrapping of single or atomic services does not consider the topology of the composition and relationships among reputation-related factors. We apply Conditional Preference Networks (CP-nets) of reputation-related factors for component services in a composition. The reputation of a composite service is bootstrapped by the composition of CP-nets. We consider the history of invocation among component services to determine reputation-interdependence in a composition. The composition rules are constructed using the composition topology and four types of reputation-influence among component services. A heuristic-based Q-learning approach is proposed to select the optimal set of reputation-related CP-nets. Experimental results prove the efficiency of the proposed approach.

Cite

@article{arxiv.2105.15135,
  title  = {Reputation Bootstrapping for Composite Services using CP-nets},
  author = {Sajib Mistry and Athman Bouguettaya},
  journal= {arXiv preprint arXiv:2105.15135},
  year   = {2021}
}

Comments

14 Pages, accepted and to appear in IEEE Transactions on Services Computing

R2 v1 2026-06-24T02:40:16.215Z