Abstract
Information retrieval on RDF data benefits greatly from additional provenance information attached to the individual pieces of information. Provenance information such as origin of data, certainty, and temporal information on RDF statements can be used to rank search results according to one of those dimensions. In this paper, we consider the problem of aggregating provenance information from different dimensions in order to obtain a joint ranking over all dimensions. We relate this to the problem of preference aggregation in social choice theory and translate different solutions for preference aggregation to the problem of aggregating provenance rankings. By exploiting the ranking orderings on the provenance dimensions, we characterize three different approaches for aggregating preferences, namely the lexicographical rule, the Borda rule and the plurality rule, in our framework of provenance aggregation.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Agrawal, S., Chaudhuri, S., Das, G., Gionis, A.: Automated Ranking of Database Query Results. In: CIDR (2003)
Arrow, K.J.: A Difficulty in the Concept of Social Welfare. Journal of Political Economy 58(4), 328–346 (1950)
Barbieri, D.F., Braga, D., Ceri, S., Della Valle, E., Grossniklaus, M.: Incremental Reasoning on Streams and Rich Background Knowledge. In: Aroyo, L., Antoniou, G., Hyvönen, E., ten Teije, A., Stuckenschmidt, H., Cabral, L., Tudorache, T. (eds.) ESWC 2010, Part I. LNCS, vol. 6088, pp. 1–15. Springer, Heidelberg (2010)
Barbieri, D.F., Braga, D., Ceri, S., Grossniklaus, M.: An Execution Environment for C-SPARQL Queries. In: EDBT, pp. 441–452. ACM (2010)
Bolles, A., Grawunder, M., Jacobi, J.: Streaming SPARQL - Extending SPARQL to Process Data Streams. In: Bechhofer, S., Hauswirth, M., Hoffmann, J., Koubarakis, M. (eds.) ESWC 2008. LNCS, vol. 5021, pp. 448–462. Springer, Heidelberg (2008)
Bruno, N., Chaudhuri, S., Gravano, L.: Top-k Selection Queries over Relational Databases: Mapping Strategies and Performance Evaluation. ACM Trans. Database Syst. 27(2), 153–187 (2002)
Buneman, P., Kostylev, E.: Annotation algebras for RDFS. In: SWPM, CEUR Workshop Proceedings (2010)
Dividino, R., Sizov, S., Staab, S., Schueler, B.: Querying for provenance, trust, uncertainty and other meta knowledge in rdf. JWS 7(3), 204–219 (2009)
Fuhr, N.: A Probabilistic Framework for Vague Queries and Imprecise Information in Databases. In: VLDB, pp. 696–707 (1990)
Gehrlein, W.V.: Condorcet’s Paradox. Theory and Decision Library C, vol. 40. Springer, Heidelberg (2006)
Green, T.J., Karvounarakis, G., Tannen, V.: Provenance semirings. In: PODS, pp. 31–40. ACM, New York (2007)
Hristidis, V., Koudas, N., Papakonstantinou, Y.: PREFER: A System for the Efficient Execution of Multi-parametric Ranked Queries. In: SIGMOD, pp. 259–270 (2001)
Ilyas, I.F., Beskales, G., Soliman, M.A.: A Survey of Top-k Query Processing Techniques in Relational Database Systems. ACM Comput. Surv. 40(4), 11:1–11:58 (2008)
Ilyas, I.F., Shah, R., Aref, W.G., Scott Vitter, J., Elmagarmid, A.K.: Rank-aware Query Optimization. In: SIGMOD, pp. 203–214 (2004)
Kelly, J.: Social Choice Theory: An Introduction. Springer (1988)
KieĂŸling, W.: Foundations of Preferences in Database Systems. In: VLDB, pp. 311–322 (2002)
Kostylev, E.V., Buneman, P.: Combining dependent annotations for relational algebra. In: ICDT, pp. 196–207. ACM, New York (2012)
Li, C., Chen-Chuan Chang, K., Ilyas, I.F., Song, S.: RankSQL: Query Algebra and Optimization for Relational Top-k Queries. In: SIGMOD, pp. 131–142 (2005)
Lopes, N., Polleres, A., Straccia, U., Zimmermann, A.: AnQL: SPARQLing Up Annotated RDFS. In: Patel-Schneider, P.F., Pan, Y., Hitzler, P., Mika, P., Zhang, L., Pan, J.Z., Horrocks, I., Glimm, B. (eds.) ISWC 2010, Part I. LNCS, vol. 6496, pp. 518–533. Springer, Heidelberg (2010)
Apostol, N., Chang, Y.-C., Smith, J.R., Li, C.-S., Vitter, J.S.: Supporting Incremental Join Queries on Ranked Inputs. In: VLDB, pp. 281–290 (2001)
Prud’hommeaux, E., Seaborne, A.: Sparql query language for rdf. W3c recommendation, W3C (January 2008)
Straccia, U., Lopes, N., LukĂ¡csy, G., Polleres, A.: A General Framework for Representing and Reasoning with Annotated Semantic Web Data. In: AAAI, pp. 1437–1442 (2010)
Xin, D., Han, J., Cheng, H., Li, X.: Answering Top-k Queries with Multi-Dimensional Selections: The Ranking Cube Approach. In: VLDB, pp. 463–475 (2006)
Zimmermann, A., Lopes, N., Polleres, A., Straccia, U.: A general framework for representing, reasoning and querying with annotated semantic web data. JWS 11(0), 72–95 (2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Dividino, R., Gröner, G., Scheglmann, S., Thimm, M. (2012). Ranking RDF with Provenance via Preference Aggregation. In: ten Teije, A., et al. Knowledge Engineering and Knowledge Management. EKAW 2012. Lecture Notes in Computer Science(), vol 7603. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33876-2_15
Download citation
DOI: https://doi.org/10.1007/978-3-642-33876-2_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33875-5
Online ISBN: 978-3-642-33876-2
eBook Packages: Computer ScienceComputer Science (R0)