Sleeman, JenniferAlonso, RafaelLi, HuaPope, ArtBadia, Antonia2018-11-142018-11-142012-04-01http://hdl.handle.net/11603/11988Proceedings of the 3rd International Workshop on Data Engineering Meets the Semantic WebOntology alignment describes a process of mapping ontological concepts, classes and attributes between different ontologies providing a way to achieve interoperability. While there has been considerable research in this area, most approaches that rely upon the alignment of attributes use label-based string comparisons of property names. The ability to process opaque or non-interpreted attribute names is a necessary component of attribute alignment. We describe a new attribute alignment approach to support ontology alignment that uses the density estimation as a means for determining alignment among objects. Using the combination of similarity hashing, Kernel Density Estimation (KDE) and Cross entropy, we are able to show promising F-Measure scores using the standard Ontology Alignment Evaluation Initiative (OAEI) 2011 benchmark.6 pagesen-USThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.ontology alignmentontologysemantic webOpaqueAttribute AlignmentUMBC Ebiquity Research GroupText