Abstract. Grid and peer-to-peer (P2P) networks are two ideal technologies for file sharing. A P2P grid is a special case of grid networks in which P2P communications are used for communication between nodes and trust management. Use of this technology allows creation of a network with greater distribution and scalability. Semantic grids have appeared as an expansion of grid networks in which rich resource metadata are revealed and clearly handled. In a semantic P2P grid, nodes are clustered into different groups based on the semantic similarities between their services. This paper proposes a reputation model for trust management in a semantic P2P Grid. We use fuzzy theory, in a trust overlay network named FR TRUST that models the network structure and the storage of reputation information. In fact we present a reputation collection and computation system for semantic P2P Grids. The system uses fuzzy theory to compute a peer trust level, which can be either: Low, Medium, or High. Our experimental results demonstrate that FR TRUST combines low (and therefore desirable) a good computational complexity with high ranking accuracy.

No abstract

Similarity is an important and fundamental concept in AI and many other fields. In different applications, users need to discover the relations between objects and find the level of semantic similarity between them. (I.e. find two similar papers or two similar events). In order to answer these types of complex queries, discovering semantic similarity association is one of the important steps. The semantic web describes the resources/entities and its relationships in machine understandable way. Although semantic web technologies define relations between objects but discovering the semantic similarity relation between objects is an ongoing research. This paper presents our method (SwSim) based on semantic association concept to discover the semantic similarity in semantic web document. In this paper, we describe how the proposed method help user to answer the complex queries in semantic web.