Generating New Features Using Genetic Programming to Detect Link Spam

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@InProceedings{Li:2011:ICICTA,
  author =       "Shengen Li and Xiaofei Niu and Peiqi Li and Lin Wang",
  title =        "Generating New Features Using Genetic Programming to
                 Detect Link Spam",
  booktitle =    "2011 International Conference on Intelligent
                 Computation Technology and Automation (ICICTA)",
  year =         "2011",
  month =        mar,
  volume =       "1",
  pages =        "135--138",
  abstract =     "Link spam techniques can enable some pages to achieve
                 higher-than-deserved rankings in the results of a
                 search engine. They negatively affect the quality of
                 search results. Classification methods can detect link
                 spam. For classification problem, features play an
                 important role. This paper proposes to derive new
                 features using genetic programming from existing
                 link-based features and use the new features as the
                 inputs to SVM and GP classifiers for the identification
                 of link spam. Experiments on WEBSPAM-UK2006 show that
                 the classification results of the classifiers that use
                 10 newly generated features are much better than those
                 of the classifiers that use original 41 link-based
                 features and equivalent to those of the classifiers
                 that use 138 transformed link-based features. The newly
                 generated features can improve the link spam
                 classification performance.",
  keywords =     "genetic algorithms, genetic programming, GP
                 classifier, SVM, WEBSPAM-UK2006, classification method,
                 link spam detection, link-based feature generation,
                 search engine, search result quality, Internet, feature
                 extraction, information retrieval, pattern
                 classification, search engines, support vector
                 machines",
  DOI =          "doi:10.1109/ICICTA.2011.41",
  notes =        "Also known as \cite{5750574}",
}

Genetic Programming entries for Shengen Li Xiaofei Niu Peiqi Li Lin Wang

Citations