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An evolutionary perspective on approximate RDF query answering

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Abstract

RDF is increasingly being used to represent large amounts of data on the Web. Current query evaluation strategies for RDF are inspired by databases, assuming perfect answers on finite repositories. In this paper, we focus on a query method based on evolutionary computing, which allows us to handle uncertainty, incompleteness and unsatisfiability, and deal with large datasets, all within a single conceptual framework. Our technique supports approximate answers with "anytime" behaviour. We present scalability results and next steps for improvement. © 2008 Springer-Verlag.
Original languageEnglish
Title of host publicationScalable Uncertainty Management - Second International Conference, SUM 2008, Proceedings
Pages215-228
Volume5291 LNAI
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event2nd International Conference on Scalable Uncertainty Management, SUM 2008 - , Italy
Duration: 1 Oct 20083 Oct 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd International Conference on Scalable Uncertainty Management, SUM 2008
Country/TerritoryItaly
Period01/10/200803/10/2008

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