Bayesian Networks Learning Algorithms for Online Form Classification
Identifieur interne : 001204 ( Hal/Corpus ); précédent : 001203; suivant : 001205Bayesian Networks Learning Algorithms for Online Form Classification
Auteurs : Emilie Philippot ; Yolande Belaïd ; Abdel BelaïdSource :
English descriptors
Abstract
In this paper a new method is presented for the recognition of online forms filled manually by a digital-type clip. This writing system transmits only the written fields without the pre-printed form. The form recognition consists in retrieving the original form directly from the filled fields without any context, which is a very challenging problem. We propose a method based on Bayesian networks. The networks use the conditional probabilities between fields in order to infer the real form. Two learning algorithms of form structures are employed to test their suitability for the case studied. The tests were conducted on the basis of 3200 forms provided by the Act image compagny, specialist in interactive writing processes. The first experiments show a recognition rate reaching more than 97%.
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DOI: 10.1109/ICPR.2010.488
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Hal:inria-00525546Le document en format XML
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This writing system transmits only the written fields without the pre-printed form. The form recognition consists in retrieving the original form directly from the filled fields without any context, which is a very challenging problem. We propose a method based on Bayesian networks. The networks use the conditional probabilities between fields in order to infer the real form. Two learning algorithms of form structures are employed to test their suitability for the case studied. The tests were conducted on the basis of 3200 forms provided by the Act image compagny, specialist in interactive writing processes. The first experiments show a recognition rate reaching more than 97%.</div></front></TEI><hal api="V3"><titleStmt><title xml:lang="en">Bayesian Networks Learning Algorithms for Online Form Classification</title><author role="aut"><persName><forename type="first">Emilie</forename><surname>Philippot</surname></persName><email>Emilie.Philippot@loria.fr</email><idno type="halauthor">501103</idno><affiliation ref="#struct-2362"></affiliation></author><author role="aut"><persName><forename type="first">Yolande</forename><surname>Belaïd</surname></persName><email>yolande.belaid@loria.fr</email><idno type="idhal">yolande-belaid</idno><idno type="halauthor">373033</idno><affiliation ref="#struct-2362"></affiliation></author><author role="aut"><persName><forename type="first">Abdel</forename><surname>Belaïd</surname></persName><email>abelaid@loria.fr</email><idno type="halauthor">52834</idno><affiliation ref="#struct-2362"></affiliation></author><editor role="depositor"><persName><forename>Yolande</forename><surname>Belaid</surname></persName><email>yolande.belaid@loria.fr</email></editor></titleStmt><editionStmt><edition n="v1" type="current"><date type="whenSubmitted">2010-10-12 10:08:51</date><date type="whenModified">2016-05-19 01:05:43</date><date type="whenReleased">2010-10-12 12:05:15</date><date type="whenProduced">2010-08-23</date><date type="whenEndEmbargoed">2010-10-12</date><ref type="file" target="https://hal.inria.fr/inria-00525546/document"><date notBefore="2010-10-12"></date></ref><ref type="file" subtype="greenPublisher" n="1" target="https://hal.inria.fr/inria-00525546/file/version_editeur_ICPR2010.pdf"><date notBefore="2010-10-12"></date></ref></edition><respStmt><resp>contributor</resp><name key="116035"><persName><forename>Yolande</forename><surname>Belaid</surname></persName><email>yolande.belaid@loria.fr</email></name></respStmt></editionStmt><publicationStmt><distributor>CCSD</distributor><idno type="halId">inria-00525546</idno><idno type="halUri">https://hal.inria.fr/inria-00525546</idno><idno type="halBibtex">philippot:inria-00525546</idno><idno type="halRefHtml">20th International Conference on Pattern Recognition- ICPR 2010, Aug 2010, Istanbul, Turkey. IEEE, pp.1981-1984, 2010, <10.1109/ICPR.2010.488></idno><idno type="halRef">20th International Conference on Pattern Recognition- ICPR 2010, Aug 2010, Istanbul, Turkey. IEEE, pp.1981-1984, 2010, <10.1109/ICPR.2010.488></idno></publicationStmt><seriesStmt><idno type="stamp" n="CNRS">CNRS - Centre national de la recherche scientifique</idno><idno type="stamp" n="INRIA">INRIA - Institut National de Recherche en Informatique et en Automatique</idno><idno type="stamp" n="LORIA2">Publications du LORIA</idno><idno type="stamp" n="LABO-LORIA-SET" p="LORIA">LABO-LORIA-SET</idno><idno type="stamp" n="LORIA">LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications</idno><idno type="stamp" n="LORIA-TALC" p="LORIA">Traitement automatique des langues et des connaissances</idno><idno type="stamp" n="UNIV-LORRAINE">Université de Lorraine</idno><idno type="stamp" n="INPL">Institut National Polytechnique de Lorraine</idno></seriesStmt><notesStmt><note type="commentary">ISSN: 1051-4651 Print ISBN: 978-1-4244-7542-1</note><note type="audience" n="2">International</note><note type="invited" n="0">No</note><note type="popular" n="0">No</note><note type="peer" n="1">Yes</note><note type="proceedings" n="1">Yes</note></notesStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Bayesian Networks Learning Algorithms for Online Form Classification</title><author role="aut"><persName><forename type="first">Emilie</forename><surname>Philippot</surname></persName><email>Emilie.Philippot@loria.fr</email><idno type="halAuthorId">501103</idno><affiliation ref="#struct-2362"></affiliation></author><author role="aut"><persName><forename type="first">Yolande</forename><surname>Belaïd</surname></persName><email>yolande.belaid@loria.fr</email><idno type="idHal">yolande-belaid</idno><idno type="halAuthorId">373033</idno><affiliation ref="#struct-2362"></affiliation></author><author role="aut"><persName><forename type="first">Abdel</forename><surname>Belaïd</surname></persName><email>abelaid@loria.fr</email><idno type="halAuthorId">52834</idno><affiliation ref="#struct-2362"></affiliation></author></analytic><monogr><meeting><title>20th International Conference on Pattern Recognition- ICPR 2010</title><date type="start">2010-08-23</date><date type="end">2010-08-26</date><settlement>Istanbul</settlement><country key="TR">Turkey</country></meeting><imprint><publisher>IEEE</publisher><biblScope unit="pp">1981-1984</biblScope><date type="datePub">2010-08-23</date></imprint></monogr><idno type="doi">10.1109/ICPR.2010.488</idno></biblStruct></sourceDesc><profileDesc><langUsage><language ident="en">English</language></langUsage><textClass><keywords scheme="author"><term xml:lang="en">Baysian network</term><term xml:lang="en">form classification</term><term xml:lang="en">on-line hand-writting</term></keywords><classCode scheme="halDomain" n="info.info-hc">Computer Science [cs]/Human-Computer Interaction [cs.HC]</classCode><classCode scheme="halDomain" n="info.info-tt">Computer Science [cs]/Document and Text Processing</classCode><classCode scheme="halDomain" n="info.info-ai">Computer Science [cs]/Artificial Intelligence [cs.AI]</classCode><classCode scheme="halTypology" n="COMM">Conference papers</classCode></textClass><abstract xml:lang="en">In this paper a new method is presented for the recognition of online forms filled manually by a digital-type clip. This writing system transmits only the written fields without the pre-printed form. The form recognition consists in retrieving the original form directly from the filled fields without any context, which is a very challenging problem. We propose a method based on Bayesian networks. The networks use the conditional probabilities between fields in order to infer the real form. Two learning algorithms of form structures are employed to test their suitability for the case studied. The tests were conducted on the basis of 3200 forms provided by the Act image compagny, specialist in interactive writing processes. The first experiments show a recognition rate reaching more than 97%.</abstract></profileDesc></hal></record>Pour manipuler ce document sous Unix (Dilib)
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