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Coverage-Based Summaries for RDF KBs

Part of the Lecture Notes in Computer Science book series (LNISA,volume 12739)


As more and more data become available as linked data, the need for efficient and effective methods for their exploration becomes apparent. Semantic summaries try to extract meaning from data, while reducing its size. State of the art structural semantic summaries, focus primarily on the graph structure of the data, trying to maximize the summary’s utility for query answering, i.e. the query coverage. In this poster paper, we present an algorithm, trying to maximize the aforementioned query coverage, using ideas borrowed from result diversification. The key idea of our algorithm is that, instead of focusing only to the “central” nodes, to push node selection also to the perimeter of the graph. Our experiments show the potential of our algorithm and demonstrate the considerable advantages gained for answering larger fragments of user queries.

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  • DOI: 10.1007/978-3-030-80418-3_18
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This research project was supported by the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the “2nd Call for H.F.R.I. Research Projects to support Post-Doctoral Researchers” (iQARuS Project No. 1147).

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Correspondence to Haridimos Kondylakis .

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Vassiliou, G., Troullinou, G., Papadakis, N., Stefanidis, K., Pitoura, E., Kondylakis, H. (2021). Coverage-Based Summaries for RDF KBs. In: , et al. The Semantic Web: ESWC 2021 Satellite Events. ESWC 2021. Lecture Notes in Computer Science(), vol 12739. Springer, Cham.

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