An Entropy-Based Approach for Preserving Diversity in Evolutionary Topical Search

Topic-based information retrieval is the process of matching a topic of interest against the resources that are indexed. An approach for retrieving topicrelevant resources is to generate queries that are able to reflect the topic of interest. Multi-objective Evolutionary Algorithms have demonstrate...

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Detalles Bibliográficos
Autores principales:	Baggio, Cecilia, Cecchini, Rocío L., Lorenzetti, Carlos M., Maguitman, Ana Gabriela
Formato:	Objeto de conferencia
Lenguaje:	Español
Publicado:	2016
Materias:	Ciencias Informáticas topic-based search multi-objective evolutionary algorithms diversity preservation Query formulation Information Search and Retrieval
Acceso en línea:	http://sedici.unlp.edu.ar/handle/10915/56850 http://45jaiio.sadio.org.ar/sites/default/files/ASAI-01_1.pdf
Aporte de:	SEDICI (UNLP) de Universidad Nacional de La Plata

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institution	Universidad Nacional de La Plata
institution_str	I-19
repository_str	R-120
collection	SEDICI (UNLP)
language	Español
topic	Ciencias Informáticas topic-based search multi-objective evolutionary algorithms diversity preservation Query formulation Information Search and Retrieval
spellingShingle	Ciencias Informáticas topic-based search multi-objective evolutionary algorithms diversity preservation Query formulation Information Search and Retrieval Baggio, Cecilia Cecchini, Rocío L. Lorenzetti, Carlos M. Maguitman, Ana Gabriela An Entropy-Based Approach for Preserving Diversity in Evolutionary Topical Search
topic_facet	Ciencias Informáticas topic-based search multi-objective evolutionary algorithms diversity preservation Query formulation Information Search and Retrieval
description	Topic-based information retrieval is the process of matching a topic of interest against the resources that are indexed. An approach for retrieving topicrelevant resources is to generate queries that are able to reflect the topic of interest. Multi-objective Evolutionary Algorithms have demonstrated great potential to deal with the problem of topical query generation. In an evolutionary approach to topic-based information retrieval the topic of interest is used to generate an initial population of queries, which is evolved towards successively better candidate queries. A common problem with such an approach is poor recall due to loss of genetic diversity. This work proposes a novel strategy inspired on the information theoretic notion of entropy to favor population diversity with the aim of attaining good global recall. Preliminary experiments conducted on a large dataset of labeled documents show the effectiveness of the proposed strategy.
format	Objeto de conferencia Objeto de conferencia
author	Baggio, Cecilia Cecchini, Rocío L. Lorenzetti, Carlos M. Maguitman, Ana Gabriela
author_facet	Baggio, Cecilia Cecchini, Rocío L. Lorenzetti, Carlos M. Maguitman, Ana Gabriela
author_sort	Baggio, Cecilia
title	An Entropy-Based Approach for Preserving Diversity in Evolutionary Topical Search
title_short	An Entropy-Based Approach for Preserving Diversity in Evolutionary Topical Search
title_full	An Entropy-Based Approach for Preserving Diversity in Evolutionary Topical Search
title_fullStr	An Entropy-Based Approach for Preserving Diversity in Evolutionary Topical Search
title_full_unstemmed	An Entropy-Based Approach for Preserving Diversity in Evolutionary Topical Search
title_sort	entropy-based approach for preserving diversity in evolutionary topical search
publishDate	2016
url	http://sedici.unlp.edu.ar/handle/10915/56850 http://45jaiio.sadio.org.ar/sites/default/files/ASAI-01_1.pdf
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An Entropy-Based Approach for Preserving Diversity in Evolutionary Topical Search

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