Designing a web spam classifier based on feature fusion in the Layered Multi-population Genetic Programming framework

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Keyhanipour:2013:FUSION,
  author =       "Amir Hosein Keyhanipour and Behzad Moshiri",
  title =        "Designing a web spam classifier based on feature
                 fusion in the Layered Multi-population Genetic
                 Programming framework",
  booktitle =    "16th International Conference on Information Fusion
                 (FUSION 2013)",
  year =         "2013",
  month =        "9-12 " # jul,
  pages =        "53--60",
  keywords =     "genetic algorithms, genetic programming, Web, Spam,
                 Classifier, Layered Multi-Population",
  URL =          "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6641335",
  abstract =     "Nowadays, Web spam pages are a critical challenge for
                 Web retrieval systems which have drastic influence on
                 the performance of such systems. Although these systems
                 try to combat the impact of spam pages on their final
                 results list, spammers increasingly use more
                 sophisticated techniques to increase the number of
                 views for their intended pages in order to have more
                 commercial success. This paper employs the recently
                 proposed Layered Multi-population Genetic Programming
                 model for Web spam detection task as well application
                 of correlation coefficient analysis for feature space
                 reduction. Based on our tentative results, the designed
                 classifier, which is based on a combination of easy to
                 compute features, has a very reasonable performance in
                 comparison with similar methods.",
  notes =        "Also known as \cite{6641335}",
}

Genetic Programming entries for Amir Hosein Keyhanipour Behzad Moshiri

Citations