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Vantage indexing is an indexing technique that belongs to the category of embedding or mapping approaches, because it maps a dissimilarity space onto a vector space such that traditional access methods can be used for querying. Each object is represented by a vector of dissimilarities to a small set of\n m<\/jats:italic>\n reference objects, called vantage objects. Querying takes place within this vector space. The retrieval performance of a system based on this technique can be improved significantly through a proper choice of vantage objects. We propose a new technique for selecting vantage objects that addresses the retrieval performance directly, and present extensive experimental results based on three data sets of different size and modality, including a comparison with other selection strategies. The results clearly demonstrate both the efficacy and scalability of the proposed approach.\n <\/jats:p>","DOI":"10.1145\/2000486.2000490","type":"journal-article","created":{"date-parts":[[2011,9,6]],"date-time":"2011-09-06T15:10:32Z","timestamp":1315321832000},"page":"1-18","update-policy":"http:\/\/dx.doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":15,"title":["Selecting vantage objects for similarity indexing"],"prefix":"10.1145","volume":"7","author":[{"given":"Reinier H.","family":"Van Leuken","sequence":"first","affiliation":[{"name":"Utrecht University, Utrecht, The Netherlands"}]},{"given":"Remco C.","family":"Veltkamp","sequence":"additional","affiliation":[{"name":"Utrecht University, Utrecht, The Netherlands"}]}],"member":"320","published-online":{"date-parts":[[2011,9,2]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/34.75509"},{"key":"e_1_2_1_2_1","volume-title":"Proceedings of the 5th ACM SIAM Symposium on Discrete Algorithms. 573--582","author":"Arya S."},{"key":"e_1_2_1_3_1","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR'04)","volume":"2","author":"Athitsos V."},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/93597.98741"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/361002.361007"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/502807.502809"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/253260.253345"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/328939.328959"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/ISM.2006.137"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/345508.345543"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-8655(03)00065-5"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/502807.502808"},{"key":"e_1_2_1_13_1","volume-title":"Proceedings of the 23rd VLDB Conference. 426--435","author":"Ciaccia P."},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/223784.223812"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/280277.280279"},{"key":"e_1_2_1_16_1","volume-title":"Proceedings of the European Conference on Computer Vision (ECCV'02)","volume":"2352","author":"Giannopoulos P."},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/602259.602266"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0031-3203(02)00326-6"},{"key":"e_1_2_1_19_1","unstructured":"Histecru G. and Farach-Colton M. 1999. 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