A Novel Graph-based Diversity-aware Rank Fusion Method Applied to Image Metasearch

  • José Solenir L. Figuerêdo Universidade Estadual de Feira de Santana http://orcid.org/0000-0003-1892-3455
  • Ana Lúcia L. Marreiros Maia Universidade Estadual de Feira de Santana
  • Rodrigo T. Calumby Universidade Estadual de Feira de Santana


While search result diversification is used to handle ambiguous or underspecified queries, rank aggregation is a widely used approach in metasearch. However, current aggregation methods assume that the input rankings are built only according to the relevance of the items, disregarding the inter-relationship between images in each ranking. Hence, these methods tend to be inadequate for diversity-oriented retrieval. In this work, we introduce a diversity-aware rank fusion method that is validated in the context of diverse image metasearch. The experimental findings indicate that the proposed method significantly improves the overall diversity of metasearch results, in comparison to the state-of-the-art positional and score-based fusion methods.
Palavras-chave: Metasearch, Ranking Aggregation, Information Retrieval, diversity-oriented retrieval, fusion method


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FIGUERÊDO, José Solenir L.; MAIA, Ana Lúcia L. Marreiros; CALUMBY, Rodrigo T.. A Novel Graph-based Diversity-aware Rank Fusion Method Applied to Image Metasearch. In: SIMPÓSIO BRASILEIRO DE BANCO DE DADOS (SBBD), 38. , 2023, Belo Horizonte/MG. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2023 . p. 324-329. ISSN 2763-8979. DOI: https://doi.org/10.5753/sbbd.2023.233400.