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

• Autores: Baggio, Cecilia; Cecchini, Rocío L.; Lorenzetti, Carlos M.; Maguitman, Ana Gabriela
• Año de publicación: 2016
• Idioma: español castellano
• Tipo de recurso: documento de conferencia
• Materia: Ciencias Informáticas; topic-based search; multi-objective evolutionary algorithms; diversity preservation; Query formulation; Information Search and Retrieval
• Institución: Universidad Nacional de La Plata

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.
Sociedad Argentina de Informática e Investigación Operativa (SADIO)