The Fundamentals of iSPARQL: A Virtual Triple Approach for Similarity-Based Semantic Web Tasks

@incollection{citeulike:2086392, abstract = {This research explores three SPARQL-based techniques to solve Semantic Web tasks that often require similarity measures, such as semantic data integration, ontology mapping, and Semantic Web service matchmaking. Our aim is to see how far it is possible to integrate customized similarity functions (CSF) into SPARQL to achieve good results for these tasks. Our first approach exploits virtual triples calling property functions to establish virtual relations among resources under comparison; the second approach uses extension functions to filter out resources that do not meet the requested similarity criteria; finally, our third technique applies new solution modifiers to post-process a SPARQL solution sequence. The semantics of the three approaches are formally elaborated and discussed. We close the paper with a demonstration of the usefulness of our iSPARQL framework in the context of a data integration and an ontology mapping experiment.}, author = {Kiefer, Christoph and Bernstein, Abraham and Stocker, Markus }, citeulike-article-id = {2086392}, doi = {10.1007/978-3-540-76298-0\_22}, journal = {The Semantic Web}, keywords = {approximate, imprecise, relaxed, sparql}, pages = {295--309}, posted-at = {2008-05-08 21:26:49}, priority = {2}, title = {The Fundamentals of iSPARQL: A Virtual Triple Approach for Similarity-Based Semantic Web Tasks}, url = {http://dx.doi.org/10.1007/978-3-540-76298-0\_22}, year = {2008} }

TY - CHAP ID - citeulike:2086392 L3 - citeulike-article-id:2086392 TI - The Fundamentals of iSPARQL: A Virtual Triple Approach for Similarity-Based Semantic Web Tasks JF - The Semantic Web SP - 295 EP - 309 N2 - This research explores three SPARQL-based techniques to solve Semantic Web tasks that often require similarity measures, such as semantic data integration, ontology mapping, and Semantic Web service matchmaking. Our aim is to see how far it is possible to integrate customized similarity functions (CSF) into SPARQL to achieve good results for these tasks. Our first approach exploits virtual triples calling property functions to establish virtual relations among resources under comparison; the second approach uses extension functions to filter out resources that do not meet the requested similarity criteria; finally, our third technique applies new solution modifiers to post-process a SPARQL solution sequence. The semantics of the three approaches are formally elaborated and discussed. We close the paper with a demonstration of the usefulness of our iSPARQL framework in the context of a data integration and an ontology mapping experiment. KW - approximate KW - imprecise KW - relaxed KW - sparql AU - Kiefer, Christoph AU - Bernstein, Abraham AU - Stocker, Markus PY - 2008/// UR - http://dx.doi.org/10.1007/978-3-540-76298-0_22 ER -