• 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