ERGP: A Combined Entity Resolution Approach with Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4221

  author =       "Chenchen Sun and Derong Shen and Yue Kou and 
                 Tiezheng Nie and Ge Yu",
  booktitle =    "11th Web Information System and Application Conference
  title =        "ERGP: A Combined Entity Resolution Approach with
                 Genetic Programming",
  year =         "2014",
  pages =        "215--220",
  abstract =     "Entities often hold more than one representation with
                 some expressive errors in different data sources in the
                 real world. Different representations and a few
                 possible expressive errors make entities identifying a
                 crucial task in data integration and data cleaning,
                 which is known as entity resolution. We propose a novel
                 approach for entity resolution using genetic
                 programming named Entity Resolution with Genetic
                 Programming (ERGP). ERGP is able to learn to get an
                 effective entity resolution classifier by combining
                 several different properties' comparisons. The
                 evaluation shows that ERGP outperforms the
                 state-of-the-art entity resolution algorithms. Above
                 all the ERGP approach is capable of setting the
                 threshold for each single comparison of an attributes'
                 pair, leaving no burden of setting thresholds to the
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/WISA.2014.46",
  month =        sep,
  notes =        "Inst. of Comput. Software, Northeastern Univ.,
                 Shenyang, China

                 Also known as \cite{7058015}",

Genetic Programming entries for Chenchen Sun Derong Shen Yue Kou Tiezheng Nie Ge Yu