RDFGrowth, a P2P annotation exchange algorithm for scalable Semantic Web applications

We present RDFGrowth, an algorithm that addresses a specific yet important scenario: large scale, end user targeted, metadata exchange P2P applications. In this scenario, peers perform browsing and querying of semantic web statements on a local database without directly generating network traffic or remote query execution. The database grows by learning from other peers in the P2P group using only a minimal amount of direct queries that are guaranteed to be executable with a low, predictable computational cost. Although full RDF graphs could be treated, the design allows a peer to learn only about resources considered interesting by a specific "community" and makes it possible to tag the received information according to individual trust rules. Inspired by well known viral distributed information techniques, the algorithm is in agreement with the RDF semantics and is specifically suited for the properties of Distributed Hash Table P2P networks. A few assessments about the app...

• Type: Conference
• Year: 2004
• Where: P2PKM
• Authors: Giovanni Tummarello, Christian Morbidoni, Joackin Petersson, Paolo Puliti, Francesco Piazza
• Keywords: Knowledge Management, Metadata Exchange P2p, P2PKM 2004, Semantic Web, Semantic Web Statements