Document (#33752)

Author

López-Herrera, A.G.
Herrera-Viedma, E.
Herrera, F.

Title

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

Source

Journal of the American Society for Information Science and Technology. 60(2009) no.6, S.1192-1207

Year

2009

Abstract

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).

Theme

Retrievalalgorithmen

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5. Petry, F.E.; Buckles, B.P.; Prabhu, D.: Fuzzy information retrieval using genetic algorithms and relevance feedback (1993) 0.12

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