@InProceedings{PedronetteTorr:2015:UnEfEs,
               author = "Pedronette, Daniel Carlos Guimar{\~a}es and Torres, Ricardo da 
                         S.",
          affiliation = "{State University of S{\~a}o Paulo (UNESP)} and {University of 
                         Campinas (UNICAMP)}",
                title = "Unsupervised Effectiveness Estimation for Image Retrieval using 
                         Reciprocal Rank Information",
            booktitle = "Proceedings...",
                 year = "2015",
               editor = "Papa, Jo{\~a}o Paulo and Sander, Pedro Vieira and Marroquim, 
                         Ricardo Guerra and Farrell, Ryan",
         organization = "Conference on Graphics, Patterns and Images, 28. (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "content-based image retrieval, unsupervised effectiveness 
                         estimation, query difficult prediction.",
             abstract = "In this paper, we present an unsupervised approach for estimating 
                         the effectiveness of image retrieval results obtained for a given 
                         query. The proposed approach does not require any training 
                         procedure and the computational efforts needed are very low, since 
                         only the top-k results are analyzed. In addition, we also discuss 
                         the use of the unsupervised measures in two novel rank aggregation 
                         methods, which assign weights to ranked lists according to their 
                         effectiveness estimation. An experimental evaluation was conducted 
                         considering different datasets and various image descriptors. 
                         Experimental results demonstrate the capacity of the proposed 
                         measures in correctly estimating the effectiveness of different 
                         queries in an unsupervised manner. The linear correlation between 
                         the proposed and widely used effectiveness evaluation measures 
                         achieves scores up to 0.86 for some descriptors.",
  conference-location = "Salvador, BA, Brazil",
      conference-year = "26-29 Aug. 2015",
                  doi = "10.1109/SIBGRAPI.2015.28",
                  url = "http://dx.doi.org/10.1109/SIBGRAPI.2015.28",
             language = "en",
                  ibi = "8JMKD3MGPBW34M/3JM939P",
                  url = "http://urlib.net/ibi/8JMKD3MGPBW34M/3JM939P",
           targetfile = "PID3767775.pdf",
        urlaccessdate = "2024, May 06"
}