Abstract
Experimental evidence accumulated over the past years indicated the importance of the ranking process in information retrieval. As for the textual documents, image ranking is a task that involves different parameters. They depend on the intrinsic characteristics of an image, but also on the indexing language used for representing its semantic content. We developed a weighting model that combines these parameters in a general scheme. Finding the best balance between the parameters is not straight-forward. Different parameter combinations leads to different rankings, which may be more or less accepted by the users. In this paper, we choose a set of test queries and present the impact of the parameters on the rank of each image. Different combinations are discussed, and the best combination is specified. For the evaluation, we follow a user-oriented approach, and compare the ranking provided by each parameter combination to the ranking given by human judgment. This is a step toward a user-centered image retrieval system, which will dynamically adapt to the user’s profile and preferences.
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Ounis, I. (2000). Toward a User-Centered Image Retrieval System. In: Ibrahim, M., Küng, J., Revell, N. (eds) Database and Expert Systems Applications. DEXA 2000. Lecture Notes in Computer Science, vol 1873. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44469-6_6
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DOI: https://doi.org/10.1007/3-540-44469-6_6
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