Accelerating Metric Filtering by Improving Bounds on Estimated Distances
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F20%3A00116699" target="_blank" >RIV/00216224:14330/20:00116699 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-030-60936-8_1" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-60936-8_1</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-60936-8_1" target="_blank" >10.1007/978-3-030-60936-8_1</a>
Alternative languages
Result language
angličtina
Original language name
Accelerating Metric Filtering by Improving Bounds on Estimated Distances
Original language description
Filtering is a fundamental strategy of metric similarity indexes to minimise the number of computed distances. Given a triple of objects for which distances of two pairs are known, the lower and upper bounds on the third distance can be set as the difference and the sum of these two already known distances, due to the triangle inequality rule of the metric space. For efficiency reasons, the tightness of bounds is crucial, but as angles within triangles of distances can be arbitrary, the worst case with zero and straight angles must also be considered for correctness. However, in data of real-life applications, the distribution of possible angles is skewed and extremes are very unlikely to occur. In this paper, we enhance the existing definition of bounds on the unknown distance with information about possible angles within triangles. We show that two lower bounds and one upper bound on each distance exist in case of limited angles. We analyse their filtering power and confirm high improvements of efficiency by experiments on several real-life datasets.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF16_019%2F0000822" target="_blank" >EF16_019/0000822: CyberSecurity, CyberCrime and Critical Information Infrastructures Center of Excellence</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Similarity Search and Applications: 13th International Conference, SISAP 2020, Copenhagen, Denmark, September 30 - October 2, 2020, Proceedings
ISBN
9783030609351
ISSN
0302-9743
e-ISSN
—
Number of pages
15
Pages from-to
3-17
Publisher name
Springer
Place of publication
Cham
Event location
Copenhagen, Dánsko
Event date
Jan 1, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000616694200001