Multi-modal Similarity Retrieval with a Shared Distributed Data
Store

D 2015

Multi-modal Similarity Retrieval with a Shared Distributed Data Store

NOVÁK, David

Basic information

Original name

Multi-modal Similarity Retrieval with a Shared Distributed Data Store

Authors

NOVÁK, David (203 Czech Republic, guarantor, belonging to the institution)

Edition

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

Publisher

Springer International Publishing

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

RIV identification code

RIV/00216224:14330/15:00081206

Organization unit

Faculty of Informatics

ISBN

978-3-319-16867-8

ISSN

DOI

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

Keywords in English

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

Abstract

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.

Links

GBP103/12/G084, research and development project

Name: Centrum pro multi-modální interpretaci dat velkého rozsahu

Investor: Czech Science Foundation

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, p. 28-37. ISBN 978-3-319-16867-8. Available from: https://dx.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 = {http://dx.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  - JOUR
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, p.~28-37. ISBN~978-3-319-16867-8. Available from: https://dx.doi.org/10.1007/978-3-319-16868-5\_{}3.

Detailed Information on Publication Record