Cache and Priority Queue Based Approximation Technique for a
Stream of Similarity Search Queries

D 2017

Cache and Priority Queue Based Approximation Technique for a Stream of Similarity Search Queries

NÁLEPA, Filip, Michal BATKO and Pavel ZEZULA

Basic information

Original name

Cache and Priority Queue Based Approximation Technique for a Stream of Similarity Search Queries

Authors

NÁLEPA, Filip (203 Czech Republic, guarantor, belonging to the institution), Michal BATKO (203 Czech Republic, belonging to the institution) and Pavel ZEZULA (203 Czech Republic, belonging to the institution)

Edition

Cham, Similarity Search and Applications : 10th International Conference, SISAP 2017, Munich, Germany, October 4-6, 2017, Proceedings, p. 17-33, 17 pp. 2017

Publisher

Springer, Cham

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Switzerland

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

Impact factor

Impact factor: 0.402 in 2005

RIV identification code

RIV/00216224:14330/17:00095026

Organization unit

Faculty of Informatics

ISBN

978-3-319-68473-4

ISSN

DOI

http://dx.doi.org/10.1007/978-3-319-68474-1_2

UT WoS

000616693000002

Keywords in English

approximate similarity search; stream of kNN queries

Abstract

V originále

Content-based similarity search techniques have been employed in a variety of today applications. In our work, we aim at the scenario when the similarity search is applied in the context of stream processing. In particular, there is a stream of query objects which need to be evaluated. Our goal is to be able to cope with the rate of incoming query objects (i.e., to reach sufficient throughput) and, at the same time, to preserve the quality of the obtained results at high levels. We propose an approximation technique for the similarity search which combines the probability of an indexed object to be a part of a query result and the time needed to examine the object. We are able to achieve better trade-off between the efficiency (processing time) and the quality (precision) of the similarity search compared to traditional priority queue based approximation techniques.

Links

GA16-18889S, research and development project

Name: Analytika pro velká nestrukturovaná data (Acronym: Big Data Analytics for Unstructured Data)

Investor: Czech Science Foundation

Citovat

NÁLEPA, Filip, Michal BATKO and Pavel ZEZULA. Cache and Priority Queue Based Approximation Technique for a Stream of Similarity Search Queries. In Christian Beecks, Felix Borutta, Peer Kröger, Thomas Seidl. Similarity Search and Applications : 10th International Conference, SISAP 2017, Munich, Germany, October 4-6, 2017, Proceedings. Cham: Springer, Cham, 2017, p. 17-33. ISBN 978-3-319-68473-4. Available from: https://dx.doi.org/10.1007/978-3-319-68474-1_2.

@inproceedings{1391457,
   author = {Nálepa, Filip and Batko, Michal and Zezula, Pavel},
   address = {Cham},
   booktitle = {Similarity Search and Applications : 10th International Conference, SISAP 2017, Munich, Germany, October 4-6, 2017, Proceedings},
   doi = {http://dx.doi.org/10.1007/978-3-319-68474-1_2},
   editor = {Christian Beecks, Felix Borutta, Peer Kröger, Thomas Seidl},
   keywords = {approximate similarity search; stream of kNN queries},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Cham},
   isbn = {978-3-319-68473-4},
   pages = {17-33},
   publisher = {Springer, Cham},
   title = {Cache and Priority Queue Based Approximation Technique for a Stream of Similarity Search Queries},
   year = {2017}
}

TY  - JOUR
ID  - 1391457
AU  - Nálepa, Filip - Batko, Michal - Zezula, Pavel
PY  - 2017
TI  - Cache and Priority Queue Based Approximation Technique for a Stream of Similarity Search Queries
PB  - Springer, Cham
CY  - Cham
SN  - 9783319684734
KW  - approximate similarity search
KW  - stream of kNN queries
N2  - Content-based similarity search techniques have been employed in a variety of today applications. In our work, we aim at the scenario when the similarity search is applied in the context of stream processing. In particular, there is a stream of query objects which need to be evaluated. Our goal is to be able to cope with the rate of incoming query objects (i.e., to reach sufficient throughput) and, at the same time, to preserve the quality of the obtained results at high levels. We propose an approximation technique for the similarity search which combines the probability of an indexed object to be a part of a query result and the time needed to examine the object. We are able to achieve better trade-off between the efficiency (processing time) and the quality (precision) of the similarity search compared to traditional priority queue based approximation techniques.
ER  -

NÁLEPA, Filip, Michal BATKO and Pavel ZEZULA. Cache and Priority Queue Based Approximation Technique for a Stream of Similarity Search Queries. In Christian Beecks, Felix Borutta, Peer Kröger, Thomas Seidl. \textit{Similarity Search and Applications : 10th International Conference, SISAP 2017, Munich, Germany, October 4-6, 2017, Proceedings}. Cham: Springer, Cham, 2017, p.~17-33. ISBN~978-3-319-68473-4. Available from: https://dx.doi.org/10.1007/978-3-319-68474-1\_{}2.

Detailed Information on Publication Record