"RIV/00216224:14330/08:00024154" . . "Springer-Verlag. (Berlin; Heidelberg)" . "380"^^ . "similarity search; bioinformatics; scalability; centralized index structure; distributed index structure; metric space; peer-to-peer network; experimental evaluation"@en . "Efficiency and Scalability Issues in Metric Access Methods"@en . "RIV/00216224:14330/08:00024154!RIV10-GA0-14330___" . . "3"^^ . . "978-3-540-75766-5" . . . "Berlin, Germany" . "The metric space paradigm has recently received attention as an important model of similarity in the area of Bioinformatics. Numerous techniques have been proposed to solve similarity (range or nearest-neighbor) queries on collections of data from metric domains. Though important representatives are outlined, this chapter is not trying to substitute existing comprehensive surveys. The main objective is to explain and prove by experiments that similarity searching is typically an expensive process which does not easily scale to very large volumes of data, thus distributed architectures able to exploit parallelism must be employed. After a review of applications using the metric space approach in the field of Bioinformatics, the chapter provides an overview of methods used for creating index structures able to speedup retrieval. In the metric space approach, only pair-wise distances between objects are quantified, so they represent the level of dissimilarity."@en . . "P(1ET100300419), P(GP201/07/P240)" . "14330" . "Efficiency and Scalability Issues in Metric Access Methods"@en . . "2"^^ . "The metric space paradigm has recently received attention as an important model of similarity in the area of Bioinformatics. Numerous techniques have been proposed to solve similarity (range or nearest-neighbor) queries on collections of data from metric domains. Though important representatives are outlined, this chapter is not trying to substitute existing comprehensive surveys. The main objective is to explain and prove by experiments that similarity searching is typically an expensive process which does not easily scale to very large volumes of data, thus distributed architectures able to exploit parallelism must be employed. After a review of applications using the metric space approach in the field of Bioinformatics, the chapter provides an overview of methods used for creating index structures able to speedup retrieval. In the metric space approach, only pair-wise distances between objects are quantified, so they represent the level of dissimilarity." . . . "Efficiency and Scalability Issues in Metric Access Methods" . . "30"^^ . . "Studies in Computational Intelligence, vol. 85" . . . . . . . "Gennaro, Claudio" . "Zezula, Pavel" . "365471" . "Dohnal, Vlastislav" . "[D89E65CCECD5]" . "Computational Intelligence in Medical Informatics" . . . . "Efficiency and Scalability Issues in Metric Access Methods" . . .