Title :
Facilitating Lightweight Consensuses in P2P Environments
Author_Institution :
IAM Group, Univ. of Southampton, Southampton
Abstract :
Traditional ontology mapping techniques are not strictly applicable in a dynamic and distributed environment (e.g. P2P and pervasive computing) in which on-the-fly alignments are sought after. We propose a theoretical framework that collaborates the logic formalisms with collaboratively created web repositories. A graph clustering algorithm is to discover, from concept definitions, the "feature" vectors that uniquely identify concepts; web repositories are used to understand the implications of these features. Such a combination solidifies an on-demand and approximate mechanism that emerges a context-dependent and task-specific consensus among heterogeneous participants of an information exchange task.
Keywords :
ontologies (artificial intelligence); peer-to-peer computing; P2P environments; graph clustering algorithm; latent semantic analysis; lightweight consensuses; ontology mapping techniques; Clustering algorithms; Collaboration; Humans; Internet; Joining processes; Logic; Motion pictures; Ontologies; Peer to peer computing; Pervasive computing; Graph clustering; Latent Semantic Analysis; Ontology mapping;
Conference_Titel :
Pervasive Computing and Applications, 2008. ICPCA 2008. Third International Conference on
Conference_Location :
Alexandria
Print_ISBN :
978-1-4244-2020-9
Electronic_ISBN :
978-1-4244-2021-6
DOI :
10.1109/ICPCA.2008.4783692