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Our strategy has low preprocessing requirements by dividing the computational cost of the preprocessing steps into several nodes over the cloud and locating the descriptors with similar dimensions value cardinalities logically close. New images are inserted into the distributed databases over the cloud efficiently, by supporting dynamical update in real-time. The proposed insertion algorithm has low computational complexity, depending exclusively on the dimensionality of descriptors and a small subset of descriptors with similar dimensions value cardinalities. Finally, an efficient query processing algorithm is proposed, where the dimensions of image descriptors are prioritized in the searching strategy, assuming that dimensions of high value cardinalities have more discriminative power than the dimensions of low ones. The computation effort of the query processing algorithm is divided into several nodes over the cloud infrastructure. In our experiments with seven publicly available datasets of image descriptors, we show that the proposed similarity search strategy outperforms competitive methods of single node, parallel and cloud-based architectures, in terms of preprocessing cost, search time and accuracy.<\/jats:p>","DOI":"10.1145\/2716315","type":"journal-article","created":{"date-parts":[[2015,6,2]],"date-time":"2015-06-02T18:19:47Z","timestamp":1433269187000},"page":"1-23","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Similarity Search over the Cloud Based on Image Descriptors' Dimensions Value Cardinalities"],"prefix":"10.1145","volume":"11","author":[{"given":"Stefanos","family":"Antaris","sequence":"first","affiliation":[{"name":"Aristotle University of Thessaloniki, Thessaloniki, Greece"}]},{"given":"Dimitrios","family":"Rafailidis","sequence":"additional","affiliation":[{"name":"Aristotle University of Thessaloniki, Thessaloniki, Greece"}]}],"member":"320","published-online":{"date-parts":[[2015,6,2]]},"reference":[{"volume-title":"Proceedings of the British Machine Vision Conference (BMVC'11)","author":"Aly M.","key":"e_1_2_2_1_1"},{"volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 3069--3076","author":"Babenko A.","key":"e_1_2_2_2_1"},{"key":"e_1_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2007.07.012"},{"key":"e_1_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2007.09.014"},{"key":"e_1_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/328939.328959"},{"key":"e_1_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/2501643.2501652"},{"key":"e_1_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.5555\/1788524.1788559"},{"key":"e_1_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/1363686.1363966"},{"key":"e_1_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/997817.997857"},{"key":"e_1_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/2379790.2379793"},{"key":"e_1_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/PL00010672"},{"volume-title":"Proceedings of the International Conference on Very Large Data Bases. 518--529","author":"Gionis A.","key":"e_1_2_2_12_1"},{"key":"e_1_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2011.5995432"},{"key":"e_1_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2011.5995518"},{"volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 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