Automated Query Learning with Wikipedia and Genetic Programming

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@Misc{DBLP:journals/corr/abs-1012-0841,
  author =       "Pekka Malo and Pyry-Antti Siitari and Ankur Sinha",
  title =        "Automated Query Learning with Wikipedia and Genetic
                 Programming",
  journal =      "CoRR",
  volume =       "abs/1012.0841",
  year =         "2010",
  bibsource =    "DBLP, http://dblp.uni-trier.de",
  howpublished = "arXiv",
  keywords =     "genetic algorithms, genetic programming, Wikipedia,
                 Information retrieval, Genetic programming, Query
                 learning, Automatic indexing, Concept recognition SVM,
                 C4.5,coevolution",
  URL =          "http://arxiv.org/abs/1012.0841",
  size =         "44 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 an essential shift from conventional
                 token based queries to concept based queries, leading
                 to an enhanced efficiency of information retrieval
                 systems. To efficiently handle the automated query
                 learning problem, we propose Wikipedia-based
                 Evolutionary Semantics (Wiki-ES) framework where
                 concept based queries are learnt using a co-evolving
                 evolutionary procedure. Learning concept based queries
                 using an intelligent evolutionary procedure yields
                 significant improvement in performance which is shown
                 through an extensive study using Reuters newswire
                 documents. Comparison of the proposed framework is
                 performed with other information retrieval systems.
                 Concept based approach has also been implemented on
                 other information retrieval systems to justify the
                 effectiveness of a transition from token based queries
                 to concept based queries.",
  notes =        "Inductive Query By Example (IQBE),TREC-11 dataset with
                 Reuters RCV1 corpus, Wiki as alternative to Cyc, ngrams
                 wikifier and a named-entity recognizer
                 (NER).Conditional Random Fields (CRF)-based classifier
                 using several individuals, JGAP, java weka, best on
                 {"}F-score{"} See \cite{Malo:2013:AI}",
}

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

Citations