Manuel Atencia, Jérôme Euzenat, Giuseppe Pirrò, Marie-Christine Rousset, Alignment-based trust for resource finding in semantic P2P networks, in: Proc. 10th conference on International semantic web conference (ISWC), Bonn (DE), (Lora Aroyo, Christopher Welty, Harith Alani, Jamie Taylor, Abraham Bernstein, Lalana Kagal, Natalya Noy, Eva Blomqvist (eds), The semantic web (Proc. 10th conference on International semantic web conference (ISWC)), Lecture notes in computer science 7031, 2011), pp51-66, 2011
In a semantic P2P network, peers use separate ontologies and rely on alignments between their ontologies for translating queries. Nonetheless, alignments may be limited -unsound or incomplete- and generate flawed translations, leading to unsatisfactory answers. In this paper we present a trust mechanism that can assist peers to select those in the network that are better suited to answer their queries. The trust that a peer has towards another peer depends on a specific query and represents the probability that the latter peer will provide a satisfactory answer. We have implemented the trust technique and conducted an evaluation. Experimental results showed that trust values converge as more queries are sent and answers received. Furthermore, the use of trust brings a gain in query-answering performance.
semantic alignment, trust, probabilistic populated ontology
Manuel Atencia, Jérôme Euzenat, Marie-Christine Rousset, Exploiting ontologies and alignments for trust in semantic P2P networks, Research report 18, LIG, Grenoble (FR), 10p., June 2011
In a semantic P2P network, peers use separate ontologies and rely on alignments between their ontologies for translating queries. However, alignments may be limited unsound or incomplete and generate flawed translations, and thereby produce unsatisfactory answers. In this paper we propose a trust mechanism that can assist peers to select those in the network that are better suited to answer their queries. The trust that a peer has towards another peer is subject to a specific query and approximates the probability that the latter peer will provide a satisfactory answer. In order to compute trust, we exploit the information provided by peers' ontologies and alignments, along with the information that comes from peers' experience. Trust values are refined over time as more queries are sent and answers received, and we prove that these approximations converge.
semantic alignment, trust, probabilistic populated ontology