"Scalable Similarity Search in Metric Spaces" . "Cagliari" . . "distributed data; scalable structures; similarity search; metric space"@en . . "213-224" . "Edizioni Progetto Padova" . . . "Batko, Michal" . . "Pre-proceedings of the Sixth Thematic Workshop of the EU Network of Excellence DELOS" . "585509" . "4"^^ . "\u0160k\u00E1lovateln\u00E9 podobnostn\u00ED hled\u00E1n\u00ED v metrick\u00FDch prostorech"@cs . . "Tento \u010Dl\u00E1nek popisuje strukturu pro distribuovan\u00E9 podobnostn\u00ED hledan\u00ED v metrick\u00FDch prostorech."@cs . "2"^^ . "Scalable Similarity Search in Metric Spaces"@en . "RIV/00216224:14610/04:00010210!RIV08-MSM-14610___" . "Zezula, Pavel" . "RIV/00216224:14610/04:00010210" . . . "2004-06-24+02:00"^^ . "Scalable Similarity Search in Metric Spaces" . . . "Gennaro, Claudio" . . "Similarity search in metric spaces represents an important paradigm for content-based retrieval of many applications. Existing centralized search structures can speed-up retrieval, but they do not scale up to large volume of data because the response time is linearly increasing with the size of the searched file. The proposed GHT* index is a scalable and distributed structure. By exploiting parallelism in a dynamic network of computers, the GHT* achieves practically constant search time for similarity range queries in data-sets of arbitrary size. The amount of replicated routing information on each server increases logarithmically. At the same time, the potential for interquery parallelism is increasing with the growing data-sets because the relative number of servers utilized by individual queries is decreasing. All these properties are verified by experiments on a prototype system using real-life data-sets."@en . . . "[4E349F0386DE]" . "Z(MSM 143300004)" . "Similarity search in metric spaces represents an important paradigm for content-based retrieval of many applications. Existing centralized search structures can speed-up retrieval, but they do not scale up to large volume of data because the response time is linearly increasing with the size of the searched file. The proposed GHT* index is a scalable and distributed structure. By exploiting parallelism in a dynamic network of computers, the GHT* achieves practically constant search time for similarity range queries in data-sets of arbitrary size. The amount of replicated routing information on each server increases logarithmically. At the same time, the potential for interquery parallelism is increasing with the growing data-sets because the relative number of servers utilized by individual queries is decreasing. All these properties are verified by experiments on a prototype system using real-life data-sets." . . "14610" . "Pasquale, Savino" . . "12"^^ . . "Scalable Similarity Search in Metric Spaces"@en . . "\u0160k\u00E1lovateln\u00E9 podobnostn\u00ED hled\u00E1n\u00ED v metrick\u00FDch prostorech"@cs . "Cagliari" . .