Content-based annotation and classification framework: a
general multi-purpose approach

D 2013

Content-based annotation and classification framework: a general multi-purpose approach

BATKO, Michal, Jan BOTOREK, Petra BUDÍKOVÁ a Pavel ZEZULA

Základní údaje

Originální název

Content-based annotation and classification framework: a general multi-purpose approach

Autoři

BATKO, Michal (203 Česká republika, domácí), Jan BOTOREK (203 Česká republika, domácí), Petra BUDÍKOVÁ (203 Česká republika, garant, domácí) a Pavel ZEZULA (203 Česká republika, domácí)

Vydání

New York, NY, USA, Proceedings of the 17th International Database Engineering & Applications Symposium, od s. 58-67, 10 s. 2013

Nakladatel

ACM

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Česká republika

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

paměťový nosič (CD, DVD, flash disk)

Kód RIV

RIV/00216224:14330/13:00065734

Organizační jednotka

Fakulta informatiky

ISBN

978-1-4503-2025-2

DOI

http://dx.doi.org/10.1145/2513591.2513651

Klíčová slova anglicky

Automatic image annotation; classication; content-based search; hierarchical approach

Štítky

core_B, DISA, firank_B

Změněno: 5. 3. 2018 20:29, RNDr. Pavel Šmerk, Ph.D.

Anotace

V originále

Unprecedented amounts of digital data are becoming available nowadays, but frequently the data lack some semantic information necessary to effectively organize these resources. For images in particular, textual annotations that represent the semantics are highly desirable. Only a small percentage of images is created with reliable annotations, therefore a lot of effort is being invested into automatic image annotation. In this paper, we address the annotation problem from a general perspective and introduce a new annotation model that is applicable to many text assignment problems. We also provide experimental results from several implemented instances of our model.

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

VF20102014004, projekt VaV

Název: Multimediální analýza (Akronym: Multimediální analýza)

Investor: Ministerstvo vnitra ČR, Multimediální analýza

Citovat

BATKO, Michal, Jan BOTOREK, Petra BUDÍKOVÁ a Pavel ZEZULA. Content-based annotation and classification framework: a general multi-purpose approach. In Proceedings of the 17th International Database Engineering & Applications Symposium. New York, NY, USA: ACM, 2013, s. 58-67. ISBN 978-1-4503-2025-2. Dostupné z: https://dx.doi.org/10.1145/2513591.2513651.

@inproceedings{1127649,
   author = {Batko, Michal and Botorek, Jan and Budíková, Petra and Zezula, Pavel},
   address = {New York, NY, USA},
   booktitle = {Proceedings of the 17th International Database Engineering & Applications Symposium},
   doi = {http://dx.doi.org/10.1145/2513591.2513651},
   keywords = {Automatic image annotation; classication; content-based search; hierarchical approach},
   howpublished = {paměťový nosič},
   language = {eng},
   location = {New York, NY, USA},
   isbn = {978-1-4503-2025-2},
   pages = {58-67},
   publisher = {ACM},
   title = {Content-based annotation and classification framework: a general multi-purpose approach},
   year = {2013}
}

TY  - JOUR
ID  - 1127649
AU  - Batko, Michal - Botorek, Jan - Budíková, Petra - Zezula, Pavel
PY  - 2013
TI  - Content-based annotation and classification framework: a general multi-purpose approach
PB  - ACM
CY  - New York, NY, USA
SN  - 9781450320252
KW  - Automatic image annotation
KW  - classication
KW  - content-based search
KW  - hierarchical approach
N2  - Unprecedented amounts of digital data are becoming available nowadays, but frequently the data lack some semantic information necessary to effectively organize these resources. For images in particular, textual annotations that represent the semantics are highly desirable. Only a small percentage of images is created with reliable annotations, therefore a lot of effort is being invested into automatic image annotation. In this paper, we address the annotation problem from a general perspective and introduce a new annotation model that is applicable to many text assignment problems. We also provide experimental results from several implemented instances of our model.
ER  -

BATKO, Michal, Jan BOTOREK, Petra BUDÍKOVÁ a Pavel ZEZULA. Content-based annotation and classification framework: a general multi-purpose approach. In \textit{Proceedings of the 17th International Database Engineering \&{} Applications Symposium}. New York, NY, USA: ACM, 2013, s.~58-67. ISBN~978-1-4503-2025-2. Dostupné z: https://dx.doi.org/10.1145/2513591.2513651.

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