Enhancing Similarity Search Throughput by Dynamic Query Reordering
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F16%3A00088102" target="_blank" >RIV/00216224:14330/16:00088102 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-44406-2_14" target="_blank" >http://dx.doi.org/10.1007/978-3-319-44406-2_14</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-44406-2_14" target="_blank" >10.1007/978-3-319-44406-2_14</a>
Alternative languages
Result language
angličtina
Original language name
Enhancing Similarity Search Throughput by Dynamic Query Reordering
Original language description
A lot of multimedia data are being created nowadays, which can only be searched by content since no searching metadata are available for them. To make the content search efficient, similarity indexing structures based on the metric-space model can be used. In our work, we focus on a scenario where the similarity search is used in the context of stream processing. In particular, there is a potentially infinite sequence (stream) of query objects, and a query needs to be executed for each of them. The goal is to maximize the throughput of processed queries while maintaining an acceptable delay. We propose an approach based on dynamic reordering of the incoming queries combined with caching of recent results. We were able to achieve up to 3.7 times higher throughput compared to the base case when no reordering and caching is used.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GA16-18889S" target="_blank" >GA16-18889S: Big Data Analytics for Unstructured Data</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Database and Expert Systems Applications: 27th International Conference, DEXA 2016, Porto, Portugal, September 5-8, 2016, Proceedings, Part II
ISBN
9783319444055
ISSN
0302-9743
e-ISSN
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Number of pages
16
Pages from-to
185-200
Publisher name
Springer International Publishing
Place of publication
Cham
Event location
Porto, Portugal
Event date
Sep 5, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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