Improving the Recall of Live Linked Data Querying through Reasoning. Umbrich, J., Hogan, A., Polleres, A., & Decker, S. In Krötzsch, M. & Straccia, U., editors, Web Reasoning and Rule Systems – 6th International Conference, RR2012, volume 7497, of Lecture Notes in Computer Science (LNCS), pages 188–204, Vienna, Austria, September, 2012. Springer.
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Paper doi abstract bibtex
Paper doi abstract bibtex Linked Data principles allow for processing SPARQL queries on-the-fly by dereferencing URIs. Link-traversal query approaches for Linked Data have the benefit of up-to-date results and decentralised execution, but operate only on explicit data from dereferenced documents, affecting recall. In this paper, we show how inferable knowledge – specifically that found through owl:sameAs and RDFS reasoning – can improve recall in this setting. We first analyse a corpus featuring 7 million Linked Data sources and 2.1 billion quadruples: we (1) measure expected recall by only considering dereferenceable information, (2) measure the improvement in recall given by considering rdfs:seeAlso links as previous proposals did. We further propose and measure the impact of additionally considering (3) owl:sameAs links, and (4) applying lightweight RDFS reasoning for finding more results, relying on static schema information. We evaluate different configurations for live queries covering different shapes and domains, generated from random walks over our corpus.
@inproceedings{umbr-etal-2012RR,
Abstract = {Linked Data principles allow for processing SPARQL queries on-the-fly by dereferencing URIs. Link-traversal query approaches for Linked Data have the benefit of up-to-date results and decentralised execution, but operate only on explicit data from dereferenced documents, affecting recall. In this paper, we show how inferable knowledge -- specifically that found through owl:sameAs and RDFS reasoning -- can improve recall in this setting. We first analyse a corpus featuring 7 million Linked Data sources and 2.1 billion quadruples: we (1) measure expected recall by only considering dereferenceable information, (2) measure the improvement in recall given by considering rdfs:seeAlso links as previous proposals did. We further propose and measure the impact of additionally considering (3) owl:sameAs links, and (4) applying lightweight RDFS reasoning for finding more results, relying on static schema information. We evaluate different configurations for live queries covering different shapes and domains, generated from random walks over our corpus.},
Address = {Vienna, Austria},
Author = {J{\"u}rgen Umbrich and Aidan Hogan and Axel Polleres and Stefan Decker},
Booktitle = {Web Reasoning and Rule Systems -- 6th International Conference, RR2012},
Day = {10--12},
Editor = {Markus Kr\"otzsch and Umberto Straccia},
Month = SEP,
Pages = {188--204},
Publisher = {Springer},
Series = LNCS,
Title = {Improving the Recall of Live Linked Data Querying through Reasoning},
Type = CONF,
doi = {10.1007/978-3-642-33203-6_14},
Url = {http://www.polleres.net/publications/umbr-etal-2012RR.pdf},
Volume = 7497,
Year = 2012,
Bdsk-Url-1 = {http://www.polleres.net/publications/umbr-etal-2012RR.pdf}}Downloads: 0
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