In this paper, we investigate the problem of assembling fragments from different graphs to build an answer to a user query. The goal is to be able to provide an answer, by aggregation, when a single graph cannot satisfy all the query constraints. We provide the underlying basic algorithms and a relational framework to support aggregated search in graph databases. Our objective is to provide a flexible framework for the integration of data whose structure is graph-based (e.g., RDF). The idea is that the user has not to specify a join operation between fragments. The way the fragments can be combined is a discovery process and rests on a specific algorithm. We also led some experiments on synthetic datasets to demonstrate the effectiveness of this approach. © 2012 Springer-Verlag.
CITATION STYLE
Le, T. H., Elghazel, H., & Hacid, M. S. (2012). A relational-based approach for aggregated search in graph databases. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7238 LNCS, pp. 33–47). https://doi.org/10.1007/978-3-642-29038-1_5
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