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Similarity search in metric spaces is a general paradigm that can be used in several application fields. It can also be effectively exploited in content-based image retrieval systems, which are shifting their target towards the Web-scale dimension. In this context, an important issue becomes the design of scalable solutions, which combine parallel and distributed architectures with caching at several levels. To this end, we investigate the design of a similarity cache that works in metricdoi:10.1145/1458469.1458473 dblp:conf/cikm/FalchiLOPR08 fatcat:4thbgn2zyrdo3apo4jutpck3l4