Similarity Join in Metric Spaces
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F03%3A00008670" target="_blank" >RIV/00216224:14330/03:00008670 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Similarity Join in Metric Spaces
Original language description
Similarity join in distance spaces constrained by the metric postulates is the necessary complement of more famous similarity range and the nearest neighbors search primitives. However, the quadratic computational complexity of similarity joins preventsfrom applications on large data collections. We first study the underlying principles of such joins and suggest three categories of implementation strategies based on filtering, partitioning, or similarity range searching. Then we study an application ofthe D-index to implement the most promising alternative of range searching. Though also this approach is not able to eliminate the intrinsic quadratic complexity of similarity joins, significant performance improvements are confirmed by experiments.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JC - Computer hardware and software
OECD FORD branch
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Result continuities
Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2003
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the European Conference on Information Retrieval Research
ISBN
3-540-01274-5
ISSN
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e-ISSN
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Number of pages
16
Pages from-to
452-467
Publisher name
Springer-Verlag
Place of publication
Berlin
Event location
Pisa, Italy
Event date
Apr 14, 2003
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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