Automated query learning with Wikipedia and genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Pekka Malo and Pyry Siitari and Ankur Sinha",
  title =        "Automated query learning with Wikipedia and genetic
  journal =      "Artificial Intelligence",
  year =         "2013",
  volume =       "194",
  pages =        "86--110",
  month =        jan,
  note =         "Special issue on Artificial Intelligence, Wikipedia
                 and Semi-Structured Resources",
  keywords =     "genetic algorithms, genetic programming, Wikipedia,
                 Concept recognition, Information filtering, Automatic
                 indexing, Query definition",
  ISSN =         "0004-3702",
  URL =          "",
  DOI =          "doi:10.1016/j.artint.2012.06.006",
  size =         "25 pages",
  abstract =     "Most of the existing information retrieval systems are
                 based on bag-of-words model and are not equipped with
                 common world knowledge. Work has been done towards
                 improving the efficiency of such systems by using
                 intelligent algorithms to generate search queries,
                 however, not much research has been done in the
                 direction of incorporating human-and-society level
                 knowledge in the queries. This paper is one of the
                 first attempts where such information is incorporated
                 into the search queries using Wikipedia semantics. The
                 paper presents Wikipedia-based Evolutionary Semantics
                 (Wiki-ES) framework for generating concept based
                 queries using a set of relevance statements provided by
                 the user. The query learning is handled by a
                 co-evolving genetic programming procedure. To evaluate
                 the proposed framework, the system is compared to a
                 bag-of-words based genetic programming framework as
                 well as to a number of alternative document filtering
                 techniques. The results obtained using Reuters newswire
                 documents are encouraging. In particular, the injection
                 of Wikipedia semantics into a GP-algorithm leads to
                 improvement in average recall and precision, when
                 compared to a similar system without human knowledge. A
                 further comparison against other document filtering
                 frameworks suggests that the proposed GP-method also
                 performs well when compared with systems that do not
                 rely on query-expression learning.",
  notes =        "Aalto University, School of Economics. See also

                 Also known as \cite{Malo201386}


Genetic Programming entries for Pekka Malo Pyry-Antti Siitari Ankur Sinha