Paper Info
Title
UFOMQ: An Algorithm for Querying for Similar Individuals in Heterogeneous Ontologies
Abstract
The chief challenge in identifying similar individuals across multiple ontologies is the high computational cost of evaluating similarity between every pair of entities. We present an approach to querying for similar individuals across multiple ontologies that makes use of the correspondences discovered during ontology alignment in order to reduce this cost. The query algorithm is designed using the framework of fuzzy logic and extends fuzzy ontology alignment. The algorithm identifies entities that are related to the given entity directly from a single alignment link or by following multiple alignment links. We evaluate the approach using both publicly available ontologies and from an enterprise-scale dataset. Experiments show that it is possible to trade-off a small decrease in precision of the query results with a large savings in execution time.
Year
DOI
Venue
2015
10.1007/978-3-319-22729-0_14
Lecture Notes in Computer Science
Field
DocType
Volume
Ontology (information science),Data mining,Ontology alignment,Computer science,Fuzzy logic,Algorithm,SPARQL,Fuzzy ontology,Execution time,Multiple sequence alignment
Conference
9263
ISSN
Citations 
PageRank 
0302-9743
0
0.34
References 
Authors
13
3
Name
Order
Citations
PageRank
Yinuo Zhang1243.76
Anand V. Panangadan2166.49
Viktor K. Prasanna37211762.74