research-article

PARIS: probabilistic alignment of relations, instances, and schema

Authors:

Fabian M. Suchanek,

Serge Abiteboul,

Pierre SenellartAuthors Info & Claims

Proceedings of the VLDB Endowment, Volume 5, Issue 3

Pages 157 - 168

https://doi.org/10.14778/2078331.2078332

Published: 01 November 2011 Publication History

Abstract

One of the main challenges that the Semantic Web faces is the integration of a growing number of independently designed ontologies. In this work, we present paris, an approach for the automatic alignment of ontologies. paris aligns not only instances, but also relations and classes. Alignments at the instance level cross-fertilize with alignments at the schema level. Thereby, our system provides a truly holistic solution to the problem of ontology alignment. The heart of the approach is probabilistic, i.e., we measure degrees of matchings based on probability estimates. This allows paris to run without any parameter tuning. We demonstrate the efficiency of the algorithm and its precision through extensive experiments. In particular, we obtain a precision of around 90% in experiments with some of the world's largest ontologies.

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cover image Proceedings of the VLDB Endowment

Proceedings of the VLDB Endowment Volume 5, Issue 3

November 2011

117 pages

ISSN:2150-8097

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VLDB Endowment

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Published: 01 November 2011

Published in PVLDB Volume 5, Issue 3

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Hofer MObraczka DSaeedi AKöpcke HRahm E(2024)Construction of Knowledge Graphs: Current State and ChallengesInformation10.3390/info1508050915:8(509)Online publication date: 22-Aug-2024
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Feng SZhou CLiu QJi XHuang M(2024)Temporal Knowledge Graph Reasoning Based on Entity Relationship Similarity PerceptionElectronics10.3390/electronics1312241713:12(2417)Online publication date: 20-Jun-2024
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