An Entropy-Based Approach for Preserving Diversity in Evolutionary Topical Search
Cecilia Baggio, Rocío L. Cecchini, Carlos M. Lorenzetti, Ana Gabriela Maguitman · El Servicio de Difusión de la Creación Intelectual (National University of La Plata) · 2016
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.