Bibliography on Semantic peer-to-peer systems/Systèmes pair-à-pair sémantiques (2017-06-06)

In this paper, we introduce a mechanism of trust adapted to semantic peer-to-peer networks in which every peer is free to organize its local resources as instances of classes of its own ontology. Peers use their ontologies to query other peers, and alignments between peers' ontologies make it possible to reformulate queries from one local peer's vocabulary to another. Alignments are typically the result of manual or (semi)automatic ontology matching. However, resulting alignments may be unsound and/or incomplete, and therefore, query reformulation based on alignments may lead to unsatisfactory answers. Trust can assist peers to select the peers in the network that are better suited to answer their queries. In our model, the trust that a peer has toward another peer depends on a specific query, and it represents the probability that the latter peer will provide a satisfactory answer to the query. In order to compute trust, we perform Bayesian inference that exploits ontologies, alignments and user feedback. We have implemented our method and conducted an evaluation. Experimental results show that trust values converge as more queries are sent and answers received. Furthermore, when query answering is guided by trust, the quality of peers' answers, measured with precision and recall, is improved.

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.

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.

Relating ontologies is very important for many ontology-based applications and more important in open environments like the semantic web. The relations between ontology entities can be obtained by ontology matching and represented as alignments. Hence, alignments must be taken into account in ontology management. This chapter establishes the requirements for alignment management. After a brief introduction to matching and alignments, we justify the consideration of alignments as independent entities and provide the life cycle of alignments. We describe the important functions of editing, managing and exploiting alignments and illustrate them with existing components.