AdaGP-Rank: Applying boosting technique to genetic programming for learning to rank

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

@InProceedings{Wang:2010:YC-ICT,
  author =       "Feng Wang2 and Xinshun Xu",
  title =        "AdaGP-Rank: Applying boosting technique to genetic
                 programming for learning to rank",
  booktitle =    "IEEE Youth Conference on Information Computing and
                 Telecommunications (YC-ICT)",
  year =         "2010",
  month =        nov,
  pages =        "259--262",
  abstract =     "One crucial task of learning to rank in the field of
                 information retrieval (IR) is to determine an ordering
                 of documents according to their degree of relevance to
                 the user given query. In this paper, a learning method
                 is proposed named AdaGP-Rank by applying boosting
                 techniques to genetic programming. This approach uses
                 genetic programming to evolve ranking functions while a
                 process inspired from AdaBoost technique helps the
                 evolved ranking functions concentrate on the ranking of
                 those documents associating those `hard' queries. Based
                 on the confidence coefficients, the ranking functions
                 obtained at each boosting round are then combined into
                 a final strong ranker. Experiments conform that
                 AdaGP-Rank has general better performance than several
                 state-of-the-art ranking algorithms on the benchmark
                 data sets.",
  keywords =     "genetic algorithms, genetic programming, AdaBoost
                 technique, AdaGP-Rank, boosting technique, confidence
                 coefficients, document ordering, information retrieval,
                 learning, user given query, document handling, learning
                 (artificial intelligence), query processing",
  DOI =          "doi:10.1109/YCICT.2010.5713094",
  notes =        "Also known as \cite{5713094}",
}

Genetic Programming entries for Feng Wang2 Xinshun Xu

Citations