How Carefully Designed Open Resource Sharing Can Help and Expand Document Analysis Research
Identifieur interne : 002811 ( Main/Exploration ); précédent : 002810; suivant : 002812How Carefully Designed Open Resource Sharing Can Help and Expand Document Analysis Research
Auteurs : Bart Lamiroy [France] ; Daniel Lopresti [États-Unis] ; Hank Korth [États-Unis] ; Jeff Heflin [États-Unis]Source :
- Proceedings of SPIE, the International Society for Optical Engineering [ 0277-786X ] ; 2011.
Descripteurs français
- Pascal (Inist)
English descriptors
Abstract
Making datasets available for peer reviewing of published document analysis methods or distributing large commonly used document corpora for benchmarking are extremely useful and sound practices and initiatives. This paper shows that they cover only a very tiny segment of the uses shared and commonly available research data may have. We develop a completely new paradigm for sharing and accessing common data sets, benchmarks and other tools that is based on a very open and free community based contribution model. The model is operational and has been implemented so that it can be tested on a brοad scale. The new interactions that will arise from its use may spark innovative ways of conducting document analysis research on the one hand, but create very challenging interactions with other research domains as well.
Affiliations:
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Eng.</title><idno type="ISSN">0277-786X</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Audio signals</term><term>Benchmarking</term><term>Document analysis</term><term>Imagery</term><term>Implementation</term><term>Resource sharing</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Imagerie</term><term>Partage des ressources</term><term>Analyse documentaire</term><term>Benchmarking</term><term>Signal audio</term><term>Implémentation</term><term>0130C</term><term>4230</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Making datasets available for peer reviewing of published document analysis methods or distributing large commonly used document corpora for benchmarking are extremely useful and sound practices and initiatives. This paper shows that they cover only a very tiny segment of the uses shared and commonly available research data may have. We develop a completely new paradigm for sharing and accessing common data sets, benchmarks and other tools that is based on a very open and free community based contribution model. The model is operational and has been implemented so that it can be tested on a brοad scale. The new interactions that will arise from its use may spark innovative ways of conducting document analysis research on the one hand, but create very challenging interactions with other research domains as well.</div></front></TEI><affiliations><list><country><li>France</li><li>États-Unis</li></country><region><li>Grand Est</li><li>Lorraine (région)</li></region><settlement><li>Vandoeuvre</li></settlement></list><tree><country name="France"><region name="Grand Est"><name sortKey="Lamiroy, Bart" sort="Lamiroy, Bart" uniqKey="Lamiroy B" first="Bart" last="Lamiroy">Bart Lamiroy</name></region></country><country name="États-Unis"><noRegion><name sortKey="Lopresti, Daniel" sort="Lopresti, Daniel" uniqKey="Lopresti D" first="Daniel" last="Lopresti">Daniel Lopresti</name></noRegion><name sortKey="Heflin, Jeff" sort="Heflin, Jeff" uniqKey="Heflin J" first="Jeff" last="Heflin">Jeff Heflin</name><name sortKey="Korth, Hank" sort="Korth, Hank" uniqKey="Korth H" first="Hank" last="Korth">Hank Korth</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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