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An Entropy-Based Approach For Preserving Diversity In Evolutionary Topical Search.pdf

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Preview of An Entropy-Based Approach for Preserving Diversity in Evolutionary Topical Search
🔗 Source: 45jaiio.sadio.org.ar
📊 Size: 236 KB
📄 Pages: 8 pages
⬇️ Downloads: 102

Summary

This work proposes a novel strategy for preserving diversity in evolutionary topical search using a multi-objective evolutionary algorithm (MOEA) framework. The approach aims to simultaneously attain topical relevance and diversity by introducing a new fitness function called entropic recall, which penalizes queries that retrieve results also retrieved by other queries in the same population. The entropic recall measure is inspired by the information theoretic notion of entropy and favors highly discriminative queries that retrieve unique resources. The proposed strategy is evaluated using classical performance metrics, such as precision and recall, as well as ad-hoc metrics designed to assess diversity and coverage of relevant results retrieved by the entire population of queries. Preliminary experiments conducted on a large dataset of labeled documents show the effectiveness of the proposed strategy in achieving good global recall and diversity.

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Description

This work proposes a novel strategy for preserving diversity in evolutionary topical search using a multi-objective evolutionary algorithm (MOEA) framework.

Technical Information

  • File Format: PDF
  • File Size: 236 KB
  • Pages: 8
  • Language: EN
  • Total Downloads: 102
  • Last Updated: 4 hours ago

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Entropy-Based guideEntropy-Based tutorialApproach guideApproach tutorialPreserving guidePreserving tutorialDiversity guideDiversity tutorialEvolutionary guideEvolutionary tutorialTopical guideTopical tutorialSearch guideSearch tutorial

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