Mining rules to align knowledge bases

Authors:
Luis A. Galárraga;Nicoleta Preda;Fabian M. Suchanek
Affiliations:
Max Planck Institute for Informatics, Saarbrücken, Germany;University of Versailles, Paris, France;Max Planck Institute for Informatics, Saarbrücken, Germany
Venue:
Proceedings of the 2013 workshop on Automated knowledge base construction
Year:
2013

Citing 16
Cited 0

Discovery of frequent DATALOG patterns

Data Mining and Knowledge Discovery
Schema Mapping as Query Discovery

VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Generic Schema Matching with Cupid

Proceedings of the 27th International Conference on Very Large Data Bases
Learning from Positive Data

ILP '96 Selected Papers from the 6th International Workshop on Inductive Logic Programming
Web-scale information extraction in knowitall: (preliminary results)

Proceedings of the 13th international conference on World Wide Web
Schema and ontology matching with COMA++

Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Yago: a core of semantic knowledge

Proceedings of the 16th international conference on World Wide Web
Leveraging data and structure in ontology integration

Proceedings of the 2007 ACM SIGMOD international conference on Management of data
AgreementMaker: efficient matching for large real-world schemas and ontologies

Proceedings of the VLDB Endowment
DBpedia: a nucleus for a web of open data

ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
OpenII: an open source information integration toolkit

Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Ontology alignment for linked open data

ISWC'10 Proceedings of the 9th international semantic web conference on The semantic web - Volume Part I
PARIS: probabilistic alignment of relations, instances, and schema

Proceedings of the VLDB Endowment
COnto-Diff: generation of complex evolution mappings for life science ontologies

Journal of Biomedical Informatics
SIGMa: simple greedy matching for aligning large knowledge bases

Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
AMIE: association rule mining under incomplete evidence in ontological knowledge bases

Proceedings of the 22nd international conference on World Wide Web

Quantified Score

Hi-index	0.00

Visualization

Abstract

The Semantic Web has made huge progress in the last decade, and now comprises hundreds of knowledge bases (KBs). The Linked Open Data cloud connects the KBs in this Web of data. However, the links between the KBs are mostly concerned with the instances, not with the schema. Aligning the schemas is not easy, because the KBs may differ not just in their names for relations and classes, but also in their inherent structure. Therefore, we argue in this paper that advanced schema alignment is needed to tie the Semantic Web together. We put forward a particularly simple approach to illustrate how that might look.