A conceptual theory of part-whole relations and its applications
Data & Knowledge Engineering - Special issue on modeling parts and wholes
Part-whole relations in object-centered systems: an overview
Data & Knowledge Engineering - Special issue on modeling parts and wholes
Automatic acquisition of hyponyms from large text corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
ACM SIGMOD Record
Automatic Discovery of Part-Whole Relations
Computational Linguistics
Ontology Matching
Espresso: leveraging generic patterns for automatically harvesting semantic relations
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Exploiting Linked Data to Build Web Applications
IEEE Internet Computing
Learning concept hierarchies from text corpora using formal concept analysis
Journal of Artificial Intelligence Research
DBpedia - A crystallization point for the Web of Data
Web Semantics: Science, Services and Agents on the World Wide Web
Concept learning in description logics using refinement operators
Machine Learning
Discovering and Maintaining Links on the Web of Data
ISWC '09 Proceedings of the 8th International Semantic Web Conference
SPARQL Query Re-writing Using Partonomy Based Transformation Rules
GeoS '09 Proceedings of the 3rd International Conference on GeoSpatial Semantics
Query Answering for OWL-DL with rules
Web Semantics: Science, Services and Agents on the World Wide Web
A better uncle for OWL: nominal schemas for integrating rules and ontologies
Proceedings of the 20th international conference on World wide web
RW'11 Proceedings of the 7th international conference on Reasoning web: semantic technologies for the web of data
A method for learning part-whole relations
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
Controlled knowledge base enrichment from web documents
WISE'12 Proceedings of the 13th international conference on Web Information Systems Engineering
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The Linked Open Data (LOD) Cloud has gained significant traction over the past few years. With over 275 interlinked datasets across diverse domains such as life science, geography, politics, and more, the LOD Cloud has the potential to support a variety of applications ranging from open domain question answering to drug discovery. Despite its significant size (approx. 30 billion triples), the data is relatively sparely interlinked (approx. 400 million links). A semantically richer LOD Cloud is needed to fully realize its potential. Data in the LOD Cloud are currently interlinked mainly via the owl:sameAs property, which is inadequate for many applications. Additional properties capturing relations based on causality or partonomy are needed to enable the answering of complex questions and to support applications. In this paper, we present a solution to enrich the LOD Cloud by automatically detecting partonomic relationships, which are well-established, fundamental properties grounded in linguistics and philosophy. We empirically evaluate our solution across several domains, and show that our approach performs well on detecting partonomic properties between LOD Cloud data.