Learning linkage rules using genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{conf/semweb/IseleB11,
  title =        "Learning linkage rules using genetic programming",
  author =       "Robert Isele and Christian Bizer",
  booktitle =    "Proceedings of the 6th International Workshop on
                 Ontology Matching",
  editor =       "Pavel Shvaiko and Jerome Euzenat and Tom Heath and 
                 Christoph Quix and Ming Mao and Isabel F. Cruz",
  year =         "2011",
  volume =       "814",
  series =       "CEUR Workshop Proceedings",
  address =      "Bonn, Germany",
  month =        oct # " 24",
  publisher =    "CEUR-WS.org",
  keywords =     "genetic algorithms, genetic programming, linked data,
                 link discovery, duplicate detection, deduplication,
                 record linkage",
  URL =          "http://ceur-ws.org/Vol-814/om2011_Tpaper2.pdf",
  URL =          "http://ceur-ws.org/Vol-814",
  size =         "12 pages",
  abstract =     "An important problem in Linked Data is the discovery
                 of links between entities which identify the same real
                 world object. These links are often generated based on
                 manually written linkage rules which specify the
                 condition which must be fulfilled for two entities in
                 order to be interlinked. In this paper, we present an
                 approach to automatically generate linkage rules from a
                 set of reference links. Our approach is based on
                 genetic programming and has been implemented in the
                 Silk Link Discovery Framework. It is capable of
                 generating complex linkage rules which compare multiple
                 properties of the entities and employ data
                 transformations in order to normalise their values.
                 Experimental results show that it outperforms a genetic
                 programming approach for record deduplication recently
                 presented by Carvalho et. al. In tests with linkage
                 rules that have been created for our research projects
                 our approach learnt rules which achieve a similar
                 accuracy than the original human-created linkage
                 rule.",
  notes =        "http://www4.wiwiss.fu-berlin.de/bizer/silk/",
  bibdate =      "2012-02-15",
  bibsource =    "DBLP,
                 http://dblp.uni-trier.de/db/conf/semweb/om2011.html#IseleB11",
}

Genetic Programming entries for Robert Isele Christian Bizer

Citations