Evolving Recurrent Linear-GP for Document Classification and Word Tracking

Created by W.Langdon from gp-bibliography.bib Revision:1.4340

  author =       "Xiao Luo and A. Nur Zincir-Heywood",
  title =        "Evolving Recurrent Linear-GP for Document
                 Classification and Word Tracking",
  booktitle =    "Proceedings of the 2006 IEEE Congress on Evolutionary
  year =         "2006",
  editor =       "Gary G. Yen and Lipo Wang and Piero Bonissone and 
                 Simon M. Lucas",
  pages =        "8605--8612",
  address =      "Vancouver",
  month =        "6-21 " # jul,
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "0-7803-9487-9",
  DOI =          "doi:10.1109/CEC.2006.1688611",
  size =         "8 pages",
  abstract =     "we propose a novel document classification system
                 where the recurrent linear Genetic Programming is
                 employed to classify the documents that are represented
                 in encoded word sequences. During this process, word
                 sequences of documents are tracked, frequent patterns
                 are detected and document is classified. We describe
                 the word encoding model and the recurrent linear
                 Genetic Programming based classification mechanism. The
                 performance results on benchmark data set Reuters 21578
                 show that this system can analyse the temporal sequence
                 patterns of a document and get competitive performance
                 on classification. We expect that it can be easily
                 applied to other application",
  notes =        "WCCI 2006 - A joint meeting of the IEEE, the EPS, and
                 the IEE.

                 IEEE Catalog Number: 06TH8846D",

Genetic Programming entries for Xiao Luo Nur Zincir-Heywood