Abstract
Many techniques were recently proposed to automate the linkage of RDF datasets. Predicate selection is the step of the linkage process that consists in selecting the smallest set of relevant predicates needed to enable instance comparison. We call keys this set of predicates that is analogous to the notion of keys in relational databases. We explain formally the different assumptions behind two existing key semantics. We then evaluate experimentally the keys by studying how discovered keys could help dataset interlinking or cleaning. We discuss the experimental results and show that the two different semantics lead to comparable results on the studied datasets.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Arasu, A., Ré, C., Suciu, D.: Large-scale deduplication with constraints using dedupalog. In: ICDE, pp. 952–963 (2009)
Atencia, M., David, J., Scharffe, F.: Keys and pseudo-keys detection for web datasets cleansing and interlinking. In: ten Teije, A., Völker, J., Handschuh, S., Stuckenschmidt, H., d’Acquin, M., Nikolov, A., Aussenac-Gilles, N., Hernandez, N. (eds.) EKAW 2012. LNCS (LNAI), vol. 7603, pp. 144–153. Springer, Heidelberg (2012)
Baxter, R., Christen, P., Churches, T.: A comparison of fast blocking methods for record linkage. In: KDD 2003 Workshops, pp. 25–27 (2003)
Elmagarmid, A.K., Ipeirotis, P.G., Verykios, V.S.: Duplicate record detection: A survey. IEEE Transactions on Knowledge and Data Engineering 19, 1–16 (2007)
Ferrara, A., Nikolov, A., Scharffe, F.: Data linking for the semantic web. Int. J. Semantic Web Inf. Syst. 7(3), 46–76 (2011)
Hu, W., Chen, J., Qu, Y.: A self-training approach for resolving object coreference on the semantic web. In: WWW, pp. 87–96 (2011)
Huhtala, Y., Kärkkäinen, J., Porkka, P., Toivonen, H.: Tane: An efficient algorithm for discovering functional and approximate dependencies. The Computer Journal 42(2), 100–111 (1999)
Isele, R., Bizer, C.: Learning expressive linkage rules using genetic programming. PVLDB 5(11), 1638–1649 (2012)
Isele, R., Jentzsch, A., Bizer, C.: Efficient multidimensional blocking for link discovery without losing recall. In: Proceedings of the 14th International Workshop on the Web and Databases (WebDB), Greece (2011)
Michelson, M., Knoblock, C.A.: Learning blocking schemes for record linkage. In: AAAI, pp. 440–445 (2006)
Ngonga Ngomo, A.-C., Lyko, K.: EAGLE: Efficient active learning of link specifications using genetic programming. In: Simperl, E., Cimiano, P., Polleres, A., Corcho, O., Presutti, V. (eds.) ESWC 2012. LNCS, vol. 7295, pp. 149–163. Springer, Heidelberg (2012)
Nikolov, A., d’Aquin, M., Motta, E.: Unsupervised learning of link discovery configuration. In: Simperl, E., Cimiano, P., Polleres, A., Corcho, O., Presutti, V. (eds.) ESWC 2012. LNCS, vol. 7295, pp. 119–133. Springer, Heidelberg (2012)
Nikolov, A., Motta, E.: Data linking: Capturing and utilising implicit schema-level relations. In: Proceedings of Linked Data on the Web Workshop at 19th International World Wide Web Conference (WWW 2010) (2010)
Patel-Schneider, P.F., Hayes, P., Horrocks, I.: OWL Web Ontology Language Semantics and Abstract Syntax Section 5. RDF-Compatible Model-Theoretic Semantics. Technical report, W3C (December 2004)
Pernelle, N., Sais, F., Symeonidou, D.: An automatic key discovery approach for data linking. Web Semantics: Science, Services and Agents on the World Wide Web (2013)
W. Recommendation. Owl 2 web ontology language: Direct semantics. In: Motik, B., Patel-Schneider, P.F., Cuenca Grau, B. (eds.) W3C (October 27, 2009), http://www.w3.org/TR/owl2-direct-semantics/
W. Recommendation. Owl 2 web ontology language: Structural specification and functional-style syntax. In: Motik, B., Patel-Schneider, P.F., Parsia, B. (eds.) W3C (October 27, 2009), http://www.w3.org/TR/owl2-syntax/
Saïs, F., Pernelle, N., Rousset, M.-C.: L2r: A logical method for reference reconciliation. In: Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, Vancouver, British Columbia, Canada, pp. 329–334 (2007)
Saïs, F., Pernelle, N., Rousset, M.-C.: Combining a logical and a numerical method for data reconciliation. In: Spaccapietra, S. (ed.) Journal on Data Semantics XII. LNCS, vol. 5480, pp. 66–94. Springer, Heidelberg (2009)
Song, D., Heflin, J.: Automatically generating data linkages using a domain-independent candidate selection approach. In: Aroyo, L., Welty, C., Alani, H., Taylor, J., Bernstein, A., Kagal, L., Noy, N., Blomqvist, E. (eds.) ISWC 2011, Part I. LNCS, vol. 7031, pp. 649–664. Springer, Heidelberg (2011)
Suchanek, F.M., Abiteboul, S., Senellart, P.: Paris: Probabilistic alignment of relations, instances, and schema. The Proceedings of the VLDB Endowment (PVLDB) 5(3), 157–168 (2011)
Volz, J., Bizer, C., Gaedke, M., Kobilarov, G.: Discovering and maintaining links on the web of data. In: Bernstein, A., Karger, D.R., Heath, T., Feigenbaum, L., Maynard, D., Motta, E., Thirunarayan, K. (eds.) ISWC 2009. LNCS, vol. 5823, pp. 650–665. Springer, Heidelberg (2009)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Atencia, M. et al. (2014). Defining Key Semantics for the RDF Datasets: Experiments and Evaluations. In: Hernandez, N., Jäschke, R., Croitoru, M. (eds) Graph-Based Representation and Reasoning. ICCS 2014. Lecture Notes in Computer Science(), vol 8577. Springer, Cham. https://doi.org/10.1007/978-3-319-08389-6_7
Download citation
DOI: https://doi.org/10.1007/978-3-319-08389-6_7
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08388-9
Online ISBN: 978-3-319-08389-6
eBook Packages: Computer ScienceComputer Science (R0)