Fusion of Big RDF Data: A Semantic Entity Resolution and Query Rewriting-based Inference Approach - Université Paris Cité Accéder directement au contenu
Communication Dans Un Congrès Année : 2015

Fusion of Big RDF Data: A Semantic Entity Resolution and Query Rewriting-based Inference Approach

Résumé

This paper presents an efficient approach to query big RDF data sources in order to get more relevant and complete results. The approach deals with two important heterogeneities in huge amount of data: semantic and URI-based entity identification heterogeneities. The paper proposes: (1) a semantic entity resolution approach based on inference mechanism to manage ambiguity of real world entities for linking data at the semantic and URI levels (2) a MapReduce-based query rewriting approach based on entity resolution results to include implicit data into query results (3) algorithms based on MapReduce paradigm to deal with huge amounts of data.
Fichier non déposé

Dates et versions

hal-01377590 , version 1 (07-10-2016)

Identifiants

  • HAL Id : hal-01377590 , version 1

Citer

Xin Huang, Salima Benbernou, Mourad Ouziri. Fusion of Big RDF Data: A Semantic Entity Resolution and Query Rewriting-based Inference Approach. wise, Nov 2015, Miami, United States. ⟨hal-01377590⟩

Collections

LIPADE UP-SCIENCES
129 Consultations
0 Téléchargements

Partager

Gmail Facebook X LinkedIn More