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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| Autores principales: | , , , |
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| Formato: | Objeto de conferencia |
| Lenguaje: | Español |
| Publicado: |
2016
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| Materias: | |
| 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: |
| Sumario: | 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. |
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