System Architecture to Implement a Conceptual Graphs Storage in an RDF Quad Store

With the growth of interest in semantics around the world, we believe that conceptual graphs have an important role to play. However, from the best of our knowledge, there is a lack of conceptual graphs storage and retrieval engine capable of scaling up. In this paper, we propose to utilize the power of the RDF stores, and present a complete system and methods to implement an efficient conceptual graphs storage and retrieval engine in an RDF store. We translate conceptual graphs knowledge bases into RDF knowledge bases, create an external index of the conceptual graphs and use the index to efficiently retrieve a set of candidate conceptual graphs in response to an expanded user query. We also discuss several heuristics which aim to speed up the data retrieval process, and present preliminary experimental results using the different heuristics.