Multi-modal Similarity Retrieval with a Shared Distributed Data
Store

D 2015

Multi-modal Similarity Retrieval with a Shared Distributed Data Store

NOVÁK, David

Základní údaje

Originální název

Multi-modal Similarity Retrieval with a Shared Distributed Data Store

Autoři

NOVÁK, David

Vydání

New York, Scalable Information Systems: 5th International Conference, INFOSCALE 2014, Seoul, South Korea, September 25-26, 2014, Revised Selected Papers, od s. 28-37, 10 s. 2015

Nakladatel

Springer International Publishing

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

tištěná verze "print"

Kód RIV

RIV/00216224:14330/15:00081206

Organizační jednotka

Fakulta informatiky

ISBN

978-3-319-16867-8

ISSN

DOI

https://doi.org/10.1007/978-3-319-16868-5_3

EID Scopus

2-s2.0-84942569886

Klíčová slova anglicky

similarity search; multi-modal search; Big Data; scalability

Štítky

DISA

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 18. 11. 2015 21:16, RNDr. David Novák, Ph.D.

Anotace

V originále

We propose a generic system architecture for large-scale similarity search in various types of digital data. The architecture combines contemporary highly-scalable distributed data stores with recent efficient similarity indexes and also with other types of search indexes. The system is designed to provide several types of queries – distance-based similarity queries, term-based queries, attribute queries, and advanced queries combining several search aspects (modalities). The first part of this work is devoted to the generic architecture and to description of a similarity index PPP-Codes that is suitable for our system. In the second part, we describe a specific instance of this architecture that manages a 106 million image collection providing content-based visual search, keyword search, attribute-based access, and their combinations.

Návaznosti

GBP103/12/G084, projekt VaV

Název: Centrum pro multi-modální interpretaci dat velkého rozsahu

Investor: Grantová agentura ČR, Centrum pro multi-modální interpretaci dat velkého rozsahu

Citovat

NOVÁK, David. Multi-modal Similarity Retrieval with a Shared Distributed Data Store. In Jung, Jason J, Badica, Costin, Kiss, Attila. Scalable Information Systems: 5th International Conference, INFOSCALE 2014, Seoul, South Korea, September 25-26, 2014, Revised Selected Papers. New York: Springer International Publishing, 2015, s. 28-37. ISBN 978-3-319-16867-8. Dostupné z: https://doi.org/10.1007/978-3-319-16868-5_3.

@inproceedings{1317715,
   author = {Novák, David},
   address = {New York},
   booktitle = {Scalable Information Systems: 5th International Conference, INFOSCALE 2014, Seoul, South Korea, September 25-26, 2014, Revised Selected Papers},
   doi = {https://doi.org/10.1007/978-3-319-16868-5_3},
   editor = {Jung, Jason J, Badica, Costin, Kiss, Attila},
   keywords = {similarity search; multi-modal search; Big Data; scalability},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {New York},
   isbn = {978-3-319-16867-8},
   pages = {28-37},
   publisher = {Springer International Publishing},
   title = {Multi-modal Similarity Retrieval with a Shared Distributed Data Store},
   year = {2015}
}

TY  - CONF
ID  - 1317715
AU  - Novák, David
PY  - 2015
TI  - Multi-modal Similarity Retrieval with a Shared Distributed Data Store
PB  - Springer International Publishing
CY  - New York
SN  - 9783319168678
KW  - similarity search
KW  - multi-modal search
KW  - Big Data
KW  - scalability
N2  - We propose a generic system architecture for large-scale similarity search in various types of digital data. The architecture combines contemporary highly-scalable distributed data stores with recent efficient similarity indexes and also with other types of search indexes. The system is designed to provide several types of queries – distance-based similarity queries, term-based queries, attribute queries, and advanced queries combining several search aspects (modalities). The first part of this work is devoted to the generic architecture and to description of a similarity index PPP-Codes that is suitable for our system. In the second part, we describe a specific instance of this architecture that manages a 106 million image collection providing content-based visual search, keyword search, attribute-based access, and their combinations.
ER  -

NOVÁK, David. Multi-modal Similarity Retrieval with a Shared Distributed Data Store. In Jung, Jason J, Badica, Costin, Kiss, Attila. \textit{Scalable Information Systems: 5th International Conference, INFOSCALE 2014, Seoul, South Korea, September 25-26, 2014, Revised Selected Papers}. New York: Springer International Publishing, 2015, s.~28-37. ISBN~978-3-319-16867-8. Dostupné z: https://doi.org/10.1007/978-3-319-16868-5\_{}3.

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