A systematic comparison of various statistical alignment models
Computational Linguistics
Ontology mapping: the state of the art
The Knowledge Engineering Review
ACM SIGMOD Record
Ontology Matching
Collective entity resolution in relational data
ACM Transactions on Knowledge Discovery from Data (TKDD)
Word alignment via quadratic assignment
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Yago: a core of semantic knowledge
Proceedings of the 16th international conference on World Wide Web
Linked data on the web (LDOW2008)
Proceedings of the 17th international conference on World Wide Web
On the Ontology Instance Matching Problem
DEXA '08 Proceedings of the 2008 19th International Conference on Database and Expert Systems Application
Ten Challenges for Ontology Matching
OTM '08 Proceedings of the OTM 2008 Confederated International Conferences, CoopIS, DOA, GADA, IS, and ODBASE 2008. Part II on On the Move to Meaningful Internet Systems
Large scale integration of senses for the semantic web
Proceedings of the 18th international conference on World wide web
Large-Scale Deduplication with Constraints Using Dedupalog
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
RiMOM: A Dynamic Multistrategy Ontology Alignment Framework
IEEE Transactions on Knowledge and Data Engineering
Ontology mapping: an information retrieval and interactive activation network based approach
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
Large-scale collective entity matching
Proceedings of the VLDB Endowment
A self-training approach for resolving object coreference on the semantic web
Proceedings of the 20th international conference on World wide web
PARIS: probabilistic alignment of relations, instances, and schema
Proceedings of the VLDB Endowment
A Survey of Indexing Techniques for Scalable Record Linkage and Deduplication
IEEE Transactions on Knowledge and Data Engineering
Mining rules to align knowledge bases
Proceedings of the 2013 workshop on Automated knowledge base construction
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The Internet has enabled the creation of a growing number of large-scale knowledge bases in a variety of domains containing complementary information. Tools for automatically aligning these knowledge bases would make it possible to unify many sources of structured knowledge and answer complex queries. However, the efficient alignment of large-scale knowledge bases still poses a considerable challenge. Here, we present Simple Greedy Matching (SiGMa), a simple algorithm for aligning knowledge bases with millions of entities and facts. SiGMa is an iterative propagation algorithm that leverages both the structural information from the relationship graph and flexible similarity measures between entity properties in a greedy local search, which makes it scalable. Despite its greedy nature, our experiments indicate that SiGMa can efficiently match some of the world's largest knowledge bases with high accuracy. We provide additional experiments on benchmark datasets which demonstrate that SiGMa can outperform state-of-the-art approaches both in accuracy and efficiency.