Abstract
Unlike traditional database management systems, in multimedia databases that support content-based retrieval over multimedia objects, it is difficult for users to express their exact information need directly in the form of a precise query. A typical interface supported by content-based retrieval systems allows users to express their query in the form of examples of objects similar to the ones they wish to retrieve. Such a user interface, however, requires mechanisms to learn the query representation from the examples provided by the user. In our previous work, we proposed a query refinement mechanism in which a query representation is modified by adding new relevant examples based on user feedback. In this paper, we describe query processing mechanisms that can efficiently support query expansion using multidimensional index structures.
This work was supported by NSF awards IIS-9734300, and CDA-9624396; in part by the Army Research Laboratory under Cooperative Agreement No. DAAL01-96-2-0003. Michael Ortega is supported in part by CONACYT grant 89061 and MAVIS fellowship.
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Porkaew, K., Mehrotra, S., Ortega, M., Chakrabarti, K. (1999). Similarity Search Using Multiple Examples in MARS. In: Huijsmans, D.P., Smeulders, A.W.M. (eds) Visual Information and Information Systems. VISUAL 1999. Lecture Notes in Computer Science, vol 1614. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48762-X_9
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DOI: https://doi.org/10.1007/3-540-48762-X_9
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