Optimization Techniques To Record Deduplication

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Deepa Karunakaran and Rangarajan Rangaswamy",
  title =        "Optimization Techniques To Record Deduplication",
  journal =      "Journal of Computer Science",
  year =         "2012",
  volume =       "8",
  number =       "9",
  pages =        "1487--1495",
  month =        aug # " 11",
  keywords =     "genetic algorithms, genetic programming, Data
                 preprocessing, remaining datasets, similarity measure
                 obtained, evaluation metrics, Artificial Bee Colony
  publisher =    "Science Publications",
  ISSN =         "1549-3636",
  bibsource =    "OAI-PMH server at www.doaj.org",
  language =     "eng",
  oai =          "oai:doaj-articles:6180e9f77d61fc46394fa6778978efc6",
  URL =          "http://www.thescipub.com/pdf/10.3844/jcssp.2012.1487.1495",
  URL =          "http://thescipub.com/abstract/10.3844/jcssp.2012.1487.1495",
  DOI =          "doi:10.3844/jcssp.2012.1487.1495",
  size =         "9 pages",
  abstract =     "Duplicate record detection is important for data
                 preprocessing and cleaning. Artificial Bee Colony (ABC)
                 is one of the most recently introduced algorithms based
                 on the intelligent foraging behaviour of a honey bee
                 swarm. Our approach to duplicate detection is the use
                 of ABC algorithm for generating the optimal similarity
                 measure to decide whether the data is duplicate or not.
                 In the training phase, ABC algorithm is used to
                 generate the optimal similarity measure. Once the
                 optimal similarity measure obtained, the deduplication
                 of remaining datasets is done with the help of optimal
                 similarity measure generated from the ABC algorithm. We
                 have used Restaurant and Cora datasets to analyse the
                 proposed algorithm and the performance of the proposed
                 algorithm is compared against the genetic programming
                 technique with the help of evaluation metrics.",

Genetic Programming entries for Deepa Karunakaran Rangarajan Rangaswamy