Context-sensitive text mining with fitness leveling Genetic Algorithm

Created by W.Langdon from gp-bibliography.bib Revision:1.4192

  author =       "Maciej Huk and Jan Kwiatkowski and 
                 Dariusz Konieczny and Michal Kedziora and Jolanta Mizera-Pietraszko",
  booktitle =    "2nd IEEE International Conference on Cybernetics
  title =        "Context-sensitive text mining with fitness leveling
                 Genetic Algorithm",
  year =         "2015",
  pages =        "342--347",
  abstract =     "Contextual processing is a great challenge for
                 information retrieval study - the most approved
                 techniques include scanning content of HTML web pages,
                 user supported metadata analysis, automatic inference
                 grounded on knowledge base, or content-oriented digital
                 documents analysis. We propose a meta-heuristic by
                 making use of Genetic Algorithms for Contextual Search
                 (GACS) built on genetic programming (GP) and custom
                 fitness levelling function to optimise contextual
                 queries in exact search that represents unstructured
                 phrases generated by the user. Our findings show that
                 the queries built with GACS can significantly optimise
                 the retrieval process.",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/CYBConf.2015.7175957",
  month =        jun,
  notes =        "Department of Computer Science, Wroclaw University of
                 Technology, Poland

                 Also known as \cite{7175957}",

Genetic Programming entries for Maciej Huk Jan Kwiatkowski Dariusz Konieczny Michal Kedziora Jolanta Mizera-Pietraszko