PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Dohnal V., Gennaro C., Zezula P. Efficiency and scalability issues in metric access methods. Kelemen Arpad, Abraham Ajith, Liang Yulan (eds.). (Studies in Computational Intelligence, vol. 85). Berlin / Heidelberg: Springer, 2008.
 
 
Abstract
(English)
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.
URL: http://www.springerlink.com/content/t728625t722x/
DOI: 10.1007/978-3-540-75767-2_12
Subject Metric spaces
Similarity search
Index structures
Sequence similarity
Bioinformatics
H.3.4 Systems and Software
H.2.2 Physical Design. Access methods


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