Finding Concept Coverings in Aligning Ontologies of Linked Data

First International Workshop on Knowledge Discovery and Data Mining Meets Linked Open Data

Rahul Parundekar ; Craig A. Knoblock ; Jose Luis Ambite

Others  :  http://ceur-ws.org/Vol-868/paper1.pdf
PID  :  43552

来源: CEUR

【 摘 要 】

Despite the recent growth in the size of the Linked DataCloud, the absence of links between the vocabularies of the sources has resulted in heterogenous schemas. Our previous work tried to nd con- ceptual mapping between two sources and was successful in nding align- ments, such as equivalence and subset relations, using the instances that are linked as equal. By using existential concepts and their intersections to dene specialized classes (restriction classes), we were able to nd alignments where previously existing concepts in one source did not have corresponding equivalent concepts in the other source. Upon inspection, we found that though we were able to nd a good number of alignments, we were unable to completely cover one source with the other. In many cases we observed that even though a larger class could be dened com- pletely by the multiple smaller classes that it subsumed, we were unable to nd these alignments because our denition of restriction classes did not contain the disjunction operator to dene a union of concepts. In this paper we propose a method that discovers alignments such as these, where a (larger) concept of the rst source is aligned to the union of the subsumed (smaller) concepts from the other source. We apply this new algorithm to the Geospatial, Biological Classication, and Genetics do- mains and show that this approach is able to discover numerous concept coverings, where (in most cases) the subsumed classes are disjoint. The resulting alignments are useful for determining the mappings between ontologies, rening existing ontologies, and nding inconsistencies that