On schema matching with opaque column names and data values
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Duplicate Record Detection: A Survey
IEEE Transactions on Knowledge and Data Engineering
Ontology Matching
Discovering Significant Patterns
Machine Learning
ACM Computing Surveys (CSUR)
Learning Concept Mappings from Instance Similarity
ISWC '08 Proceedings of the 7th International Conference on The Semantic Web
Refining Instance Coreferencing Results Using Belief Propagation
ASWC '08 Proceedings of the 3rd Asian Semantic Web Conference on The Semantic Web
Large scale integration of senses for the semantic web
Proceedings of the 18th international conference on World wide web
RiMOM: A Dynamic Multistrategy Ontology Alignment Framework
IEEE Transactions on Knowledge and Data Engineering
L2R: a logical method for reference reconciliation
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Ontology matching with semantic verification
Web Semantics: Science, Services and Agents on the World Wide Web
Sig.ma: live views on the web of data
Proceedings of the 19th international conference on World wide web
An empirical study of instance-based ontology matching
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
Sindice.com: weaving the open linked data
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
Semi-supervised learning by disagreement
Knowledge and Information Systems
ISWC'10 Proceedings of the 9th international semantic web conference on The semantic web - Volume Part I
When owl: sameAs isn't the same: an analysis of identity in linked data
ISWC'10 Proceedings of the 9th international semantic web conference on The semantic web - Volume Part I
A string metric for ontology alignment
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
Leveraging terminological structure for object reconciliation
ESWC'10 Proceedings of the 7th international conference on The Semantic Web: research and Applications - Volume Part II
OWL reasoning with WebPIE: calculating the closure of 100 billion triples
ESWC'10 Proceedings of the 7th international conference on The Semantic Web: research and Applications - Volume Part I
Automatically generating data linkages using a domain-independent candidate selection approach
ISWC'11 Proceedings of the 10th international conference on The semantic web - Volume Part I
PARIS: probabilistic alignment of relations, instances, and schema
Proceedings of the VLDB Endowment
Web Semantics: Science, Services and Agents on the World Wide Web
An empirical survey of Linked Data conformance
Web Semantics: Science, Services and Agents on the World Wide Web
Unsupervised learning of link discovery configuration
ESWC'12 Proceedings of the 9th international conference on The Semantic Web: research and applications
Towards fuzzy query-relaxation for RDF
ESWC'12 Proceedings of the 9th international conference on The Semantic Web: research and applications
Data linking with ontology alignment
ESWC'12 Proceedings of the 9th international conference on The Semantic Web: research and applications
Learning complex mappings between ontologies
JIST'11 Proceedings of the 2011 joint international conference on The Semantic Web
An effective rule miner for instance matching in a web of data
Proceedings of the 21st ACM international conference on Information and knowledge management
LINDA: distributed web-of-data-scale entity matching
Proceedings of the 21st ACM international conference on Information and knowledge management
A machine learning approach for instance matching based on similarity metrics
ISWC'12 Proceedings of the 11th international conference on The Semantic Web - Volume Part I
ISWC'12 Proceedings of the 11th international conference on The Semantic Web - Volume Part II
Data Linking for the Semantic Web
International Journal on Semantic Web & Information Systems
Accuracy vs. Speed: Scalable Entity Coreference on the Semantic Web with On-the-Fly Pruning
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Discovering interesting information with advances in web technology
ACM SIGKDD Explorations Newsletter
SIGMa: simple greedy matching for aligning large knowledge bases
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Fria: fast and robust instance alignment
Proceedings of the 22nd international conference on World Wide Web companion
Active learning of expressive linkage rules using genetic programming
Web Semantics: Science, Services and Agents on the World Wide Web
An automatic key discovery approach for data linking
Web Semantics: Science, Services and Agents on the World Wide Web
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An object on the Semantic Web is likely to be denoted with multiple URIs by different parties. Object coreference resolution is to identify "equivalent" URIs that denote the same object. Driven by the Linking Open Data (LOD) initiative, millions of URIs have been explicitly linked with owl:sameAs statements, but potentially coreferent ones are still considerable. Existing approaches address the problem mainly from two directions: one is based upon equivalence inference mandated by OWL semantics, which finds semantically coreferent URIs but probably omits many potential ones; the other is via similarity computation between property-value pairs, which is not always accurate enough. In this paper, we propose a self-training approach for object coreference resolution on the Semantic Web, which leverages the two classes of approaches to bridge the gap between semantically coreferent URIs and potential candidates. For an object URI, we firstly establish a kernel that consists of semantically coreferent URIs based on owl:sameAs, (inverse) functional properties and (max-)cardinalities, and then extend such kernel iteratively in terms of discriminative property-value pairs in the descriptions of URIs. In particular, the discriminability is learnt with a statistical measurement, which not only exploits key characteristics for representing an object, but also takes into account the matchability between properties from pragmatics. In addition, frequent property combinations are mined to improve the accuracy of the resolution. We implement a scalable system and demonstrate that our approach achieves good precision and recall for resolving object coreference, on both benchmark and large-scale datasets.