Automatic Text Summarization Using: Hybrid Fuzzy GA-GP

Created by W.Langdon from gp-bibliography.bib Revision:1.4208

  author =       "Arman Kiani-B and M. R. Akbarzadeh-T",
  title =        "Automatic Text Summarization Using: Hybrid Fuzzy
  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 =        "5465--5471",
  address =      "Vancouver",
  month =        "6-21 " # jul,
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "0-7803-9487-9",
  DOI =          "doi:10.1109/FUZZY.2006.1681829",
  size =         "7 pages",
  abstract =     "A novel technique is proposed for summarising text
                 using a combination of Genetic Algorithms (GA) and
                 Genetic Programming (GP) to optimise rule sets and
                 membership functions of fuzzy systems. The novelty of
                 the proposed algorithm is that fuzzy system is
                 optimized for extractive based text summarizing. In
                 this method GP is used for structural part and GA for
                 the string part (Membership functions). The goal is to
                 develop an optimal intelligent system to extract
                 important sentences in the texts by reducing the
                 redundancy of data. The method is applied in 3 test
                 documents and compared with the standard fuzzy systems
                 as well as two other commercial summarisers: Microsoft
                 word and Copernic Summarizer. Simulations demonstrate
                 several significant improvements with the proposed
  notes =        "WCCI 2006 - A joint meeting of the IEEE, the EPS, and
                 the IEE.

                 IEEE Catalog Number: 06TH8846D",

Genetic Programming entries for Arman Kiani-B Mohammad-R Akbarzadeh-Totonchi