DocumentCode :
124144
Title :
Locality-Sensitive Hashing for Massive String-Based Ontology Matching
Author :
Cochez, Michael
Author_Institution :
Dept. of Math. Inf. Technol., Univ. of Jyvaskyla, Jyvaskyla, Finland
Volume :
1
fYear :
2014
fDate :
11-14 Aug. 2014
Firstpage :
134
Lastpage :
140
Abstract :
This paper reports initial research results related to the use of locality-sensitive hashing (LSH) for string-based matching of big ontologies. Two ways of transforming the matching problem into a LSH problem are proposed and experimental results are reported. The performed experiments show that using LSH for ontology matching could lead to a very fast matching process. The quality of the alignment achieved in these experiments is comparable to state-of-the-art matchers, but much faster. Further research is needed to find out whether the use of different metrics or specific hardware would improve the results.
Keywords :
file organisation; ontologies (artificial intelligence); string matching; LSH problem; locality-sensitive hashing; string-based ontology matching; Concrete; Gold; Hardware; Java; Measurement; Ontologies; Standards; Big Data; Locality Sensitive Hashing; Ontology Matching;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Intelligence (WI) and Intelligent Agent Technologies (IAT), 2014 IEEE/WIC/ACM International Joint Conferences on
Conference_Location :
Warsaw
Type :
conf
DOI :
10.1109/WI-IAT.2014.26
Filename :
6927535
Link To Document :
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