Inferring Same-As Facts from Linked Data: An Iterative Import-by-Query Approach
DOI:
https://doi.org/10.1609/aaai.v29i1.9174Keywords:
Linked Open Data data linkage forward and backward reasoning Datalog rules external queriesAbstract
In this paper we model the problem of data linkage in Linked Data as a reasoning problem on possibly decentralized data. We describe a novel import-by-query algorithm that alternates steps of sub-query rewriting and of tailored querying the Linked Data cloud in order to import data as specific as possible for inferring or contradicting given target same-as facts. Experiments conducted on a real-world dataset have demonstrated the feasibility of this approach and its usefulness in practice for data linkage and disambiguation.
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Published
2015-02-09
How to Cite
Al-Bakri, M., Atencia, M., Lalande, S., & Rousset, M.-C. (2015). Inferring Same-As Facts from Linked Data: An Iterative Import-by-Query Approach. Proceedings of the AAAI Conference on Artificial Intelligence, 29(1). https://doi.org/10.1609/aaai.v29i1.9174
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Section
AAAI Technical Track: AI and the Web