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English Information

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Authors
# Name
1 José Figuerêdo(jslfigueredo@ecomp.uefs.br)
2 Ana Maia(anamarreiros@gmail.com)
3 Rodrigo Calumby(rtcalumby@ecomp.uefs.br)

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Reference
# Reference
1 Aslam, J. A. and Montague, M. (2001). Models for metasearch. In Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, page 276–284, New York, NY, USA. Association for Computing Machinery.
2 Calumby, R. T., Gonçalves, M. A., and da Silva Torres, R. (2017). Diversity-based interactive learning meets multimodality. Neurocomputing, 259:159–175. Multimodal Media Data Understanding and Analytics.
3 Dwork, C., Kumar, R., Naor, M., and Sivakumar, D. (2001). Rank aggregation methods for the web. In Proceedings of the 10th International Conference on World Wide Web, page 613–622, New York, NY, USA. ACM.
4 Figuerêdo, J. and Calumby, R. (2019). Unsupervised rank fusion for diverse image metasearch. In Anais do XXXIV Simpósio Brasileiro de Banco de Dados, pages 265– 270, Porto Alegre, RS, Brasil. SBC.
5 Liang, S., Ren, Z., and de Rijke, M. (2014). Fusion helps diversification. SIGIR ’14, page 303–312, New York, NY, USA. ACM.
6 McDonald, G., Macdonald, C., and Ounis, I. (2022). Search results diversification for effective fair ranking in academic search. Information Retrieval Journal, 25(1):1–26.
7 Ramírez-de-la-Rosa, G. et al. (2018). Overview of the multimedia information processing for personality & social networks analysis contest. In ICPR’18, Beijing, China, August 20-24, pages 127–139.
8 Vargas Muñoz, J. A., da Silva Torres, R., and Gonçalves, M. A. (2015). A soft computing approach for learning to aggregate rankings. page 83–92, New York, NY, USA. ACM.
9 Xu, C. andWu, S. (2017). The early fusion strategy for search result diversification. ACM TUR-C ’17, New York, NY, USA. ACM.
10 Yigit-Sert, S., Altingovde, I. S., Macdonald, C., Ounis, I., and Özgür Ulusoy (2020). Supervised approaches for explicit search result diversification. Information Processing & Management, 57(6):102356.