Extracting Trustworthiness Tendencies Using the Frequency Increase Metric

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2011

Autores

urbano, j (Autor) Outra; rocha, ap (Autor) FEUP; oliveira, e (Autor) FEUP

Ata de Conferência Internacional

Título: ICEIS

Páginas: 208-221

Enterprise Information Systems - 12th International Conference, ICEIS 2010, Funchal, Madeira, Portugal, June 8-12, 2010, Revised Selected Papers

Indexação

ISI Web of Knowledge - 2 Citações

Scopus - 2 Citações

Classificação Científica

FOS: Ciências exactas e naturais > Ciências da computação e da informação

Outras Informações

ID Authenticus: P-002-XFH

DOI: 10.1007/978-3-642-19802-1_15

Abstract (EN): Computational trust systems are currently considered enabler tools for the automation and the general acceptance of global electronic business-to-business processes, such as the sourcing and the selection of business partners outside the sphere of relationships of the selector. However, most of the existing trust models use simple statistical techniques to aggregate trust evidences into trustworthiness scores, and do not take context into consideration. In this paper we propose a situation-aware trust model composed of two components: Sinalpha, an aggregator engine that embeds properties of the dynamics of trust; and CF, a technique that extracts failure tendencies of agents from the history of their past events, complementing the value derived from Sinalpha with contextual information. We experimentally compared our trust model with and without the CF technique. The results obtained allow us to conclude that the consideration of context is of vital importance in order to perform more accurate selection decisions.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 14