An evolutionary approach for combining different sources of evidence in search engines

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

@Article{Silva2009276,
  author =       "Thomaz Philippe C. Silva and 
                 Edleno {Silva de Moura} and Joao Marcos B. Cavalcanti and 
                 Altigran S. {da Silva} and Moises {Gomes de Carvalho} and 
                 Marcos Andre Goncalves",
  title =        "An evolutionary approach for combining different
                 sources of evidence in search engines",
  journal =      "Information Systems",
  volume =       "34",
  number =       "2",
  pages =        "276--289",
  year =         "2009",
  ISSN =         "0306-4379",
  DOI =          "DOI:10.1016/j.is.2008.07.003",
  URL =          "http://www.sciencedirect.com/science/article/B6V0G-4T4HP8N-1/2/3258fa63377a3abe2d62f197d61bd917",
  keywords =     "genetic algorithms, genetic programming, Ranking
                 functions, Combining sources of evidence",
  abstract =     "Modern Web search engines use different strategies to
                 improve the overall quality of their document rankings.
                 Usually the strategy adopted involves the combination
                 of multiple sources of relevance into a single ranking.
                 This work proposes the use of evolutionary techniques
                 to derive good evidence combination functions using
                 three different sources of evidence of relevance: the
                 textual content of documents, the reputation of
                 documents extracted from the connectivity information
                 available in the processed collection and the anchor
                 text concatenation. The combination functions
                 discovered by our evolutionary strategies were tested
                 using a collection containing 368 queries extracted
                 from a real nation-wide search engine query log with
                 over 12 million documents. The experiments performed
                 indicate that our proposal is an effective and
                 practical alternative for combining sources of evidence
                 into a single ranking. We also show that different
                 types of queries submitted to a search engine can
                 require different combination functions and that our
                 proposal is useful for coping with such differences.",
}

Genetic Programming entries for Thomaz Philippe C Silva Edleno Silva de Moura Joao Marcos B Cavalcanti Altigran S da Silva Moises G de Carvalho Marcos Andre Goncalves

Citations