Evolving disjunctive and conjunctive topical queries based on multi-objective optimization criteria

In this work we propose techniques based on single - and multi-objective evolutionary algorithms to automatically evolve a population of topical queries. The developed techniques can be applied in the implementation of a topical search system. We report on the results of different strategies that at...

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Detalles Bibliográficos
Autores: Cecchini, Rocío Luján, Lorenzetti, Carlos Martin, Maguitman, Ana Gabriela
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2009
País:Argentina
Institución:Consejo Nacional de Investigaciones Científicas y Técnicas
Repositorio:CONICET Digital (CONICET)
Idioma:inglés
OAI Identifier:oai:ri.conicet.gov.ar:11336/75523
Acceso en línea:http://hdl.handle.net/11336/75523
Access Level:acceso abierto
Palabra clave:CONJUNCTIVE QUERIES
DISJUNCTIVE QUERIES
MULTI-OBJECTIVE EVOLUTIONARY ALGORITHMS
TOPICAL SEARCH
https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
Descripción
Sumario:In this work we propose techniques based on single - and multi-objective evolutionary algorithms to automatically evolve a population of topical queries. The developed techniques can be applied in the implementation of a topical search system. We report on the results of different strategies that attempt to evolve conjunctive and disjunctive queries. Our analysis reveals the limitations of the single-objective approach and highlights the advantages of applying multi-objective evolutionary algorithms for the problem at hand. In addition, we observe that disjunctive queries have the potential to achieve better retrieval performance than conjunctive queries. Finally, we show that the multi-objective evolutionary approach results in better performance than a baseline and other state-of-the-art techniques for query refinement.