TY - GEN
T1 - Coverage-Based Summaries for RDF KBs
AU - Vassiliou, Giannis
AU - Troullinou, Georgia
AU - Papadakis, Nikos
AU - Stefanidis, Kostas
AU - Pitoura, Evangelia
AU - Kondylakis, Haridimos
N1 - Funding Information:
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).
Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
jufoid=62555
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
U2 - 10.1007/978-3-030-80418-3_18
DO - 10.1007/978-3-030-80418-3_18
M3 - Conference contribution
AN - SCOPUS:85115847856
SN - 9783030804176
T3 - Lecture Notes in Computer Science
SP - 98
EP - 102
BT - The Semantic Web
A2 - Verborgh, Ruben
A2 - Dimou, Anastasia
A2 - Hogan, Aidan
A2 - d’Amato, Claudia
A2 - Tiddi, Ilaria
A2 - Bröring, Arne
A2 - Maier, Simon
A2 - Ongenae, Femke
A2 - Tommasini, Riccardo
A2 - Alam, Mehwish
PB - Springer
T2 - Extended Semantic Web Conference
Y2 - 6 June 2021 through 10 June 2021
ER -