A study of the use of multi-objective evolutionary algorithms to learn Boolean queries: A comparative study

نویسندگان

  • Antonio Gabriel López-Herrera
  • Enrique Herrera-Viedma
  • Francisco Herrera
چکیده

In this article, our interest is focused on the automatic learning of Boolean queries in information retrieval systems (IRSs) by means of multi-objective evolutionary algorithms considering the classic performance criteria, precision and recall. We present a comparative study of four well-known, general-purpose, multi-objective evolutionary algorithms to learn Boolean queries in IRSs. These evolutionary algorithms are the Nondominated Sorting Genetic Algorithm (NSGA-II), the first version of the Strength Pareto Evolutionary Algorithm (SPEA), the second version of SPEA (SPEA2), and the Multi-Objective Genetic Algorithm (MOGA).

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عنوان ژورنال:
  • JASIST

دوره 60  شماره 

صفحات  -

تاریخ انتشار 2009