An Efficient Form Classification Method Using Partial Matching
Identifieur interne : 002B45 ( Istex/Corpus ); précédent : 002B44; suivant : 002B46An Efficient Form Classification Method Using Partial Matching
Auteurs : Yungcheol Byun ; Sungsoo Yoon ; Yeongwoo Choi ; Gyeonghwan Kim ; Yillbyung LeeSource :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2001.
Abstract
Abstract: In this paper, we are proposing an efficient method of classifying form that is applicable in real life. Our method will identify a small number of local regions by their distinctive images with respect to their layout structure and then by using the DP (Dynamic Programming) matching to match only these local regions. The disparity score in each local region is defined and measured to select the matching regions. Genetic Algorithm will also be applied to select the best regions of matching from the viewpoint of a performance. Our approach of searching and matching only a small number of structurally distinctive local regions would reduce the processing time and yield a high rate of classification.
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DOI: 10.1007/3-540-45656-2_9
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<record><TEI wicri:istexFullTextTei="biblStruct:series"><teiHeader><fileDesc><titleStmt><title xml:lang="en">An Efficient Form Classification Method Using Partial Matching</title><author><name sortKey="Byun, Yungcheol" sort="Byun, Yungcheol" uniqKey="Byun Y" first="Yungcheol" last="Byun">Yungcheol Byun</name><affiliation><mods:affiliation>Dept. of Computer Software Research Laboratory, ETRI, Korea</mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: bcart@csai.yonsei.ac.kr</mods:affiliation></affiliation></author><author><name sortKey="Yoon, Sungsoo" sort="Yoon, Sungsoo" uniqKey="Yoon S" first="Sungsoo" last="Yoon">Sungsoo Yoon</name><affiliation><mods:affiliation>Dept. of Computer Science, Yonsei University, Korea</mods:affiliation></affiliation></author><author><name sortKey="Choi, Yeongwoo" sort="Choi, Yeongwoo" uniqKey="Choi Y" first="Yeongwoo" last="Choi">Yeongwoo Choi</name><affiliation><mods:affiliation>Dept. of Computer Science, Sookmyung Women’s University, Korea</mods:affiliation></affiliation></author><author><name sortKey="Kim, Gyeonghwan" sort="Kim, Gyeonghwan" uniqKey="Kim G" first="Gyeonghwan" last="Kim">Gyeonghwan Kim</name><affiliation><mods:affiliation>Dept. of Electronic Engineering, Sogang University, Korea</mods:affiliation></affiliation></author><author><name sortKey="Lee, Yillbyung" sort="Lee, Yillbyung" uniqKey="Lee Y" first="Yillbyung" last="Lee">Yillbyung Lee</name><affiliation><mods:affiliation>Dept. of Computer Science, Yonsei University, Korea</mods:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">ISTEX</idno><idno type="RBID">ISTEX:11745BF5D1DA066A522379204279A822EB900FD9</idno><date when="2001" year="2001">2001</date><idno type="doi">10.1007/3-540-45656-2_9</idno><idno type="url">https://api.istex.fr/document/11745BF5D1DA066A522379204279A822EB900FD9/fulltext/pdf</idno><idno type="wicri:Area/Istex/Corpus">002B45</idno></publicationStmt><sourceDesc><biblStruct><analytic><title level="a" type="main" xml:lang="en">An Efficient Form Classification Method Using Partial Matching</title><author><name sortKey="Byun, Yungcheol" sort="Byun, Yungcheol" uniqKey="Byun Y" first="Yungcheol" last="Byun">Yungcheol Byun</name><affiliation><mods:affiliation>Dept. of Computer Software Research Laboratory, ETRI, Korea</mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: bcart@csai.yonsei.ac.kr</mods:affiliation></affiliation></author><author><name sortKey="Yoon, Sungsoo" sort="Yoon, Sungsoo" uniqKey="Yoon S" first="Sungsoo" last="Yoon">Sungsoo Yoon</name><affiliation><mods:affiliation>Dept. of Computer Science, Yonsei University, Korea</mods:affiliation></affiliation></author><author><name sortKey="Choi, Yeongwoo" sort="Choi, Yeongwoo" uniqKey="Choi Y" first="Yeongwoo" last="Choi">Yeongwoo Choi</name><affiliation><mods:affiliation>Dept. of Computer Science, Sookmyung Women’s University, Korea</mods:affiliation></affiliation></author><author><name sortKey="Kim, Gyeonghwan" sort="Kim, Gyeonghwan" uniqKey="Kim G" first="Gyeonghwan" last="Kim">Gyeonghwan Kim</name><affiliation><mods:affiliation>Dept. of Electronic Engineering, Sogang University, Korea</mods:affiliation></affiliation></author><author><name sortKey="Lee, Yillbyung" sort="Lee, Yillbyung" uniqKey="Lee Y" first="Yillbyung" last="Lee">Yillbyung Lee</name><affiliation><mods:affiliation>Dept. of Computer Science, Yonsei University, Korea</mods:affiliation></affiliation></author></analytic><monogr></monogr><series><title level="s">Lecture Notes in Computer Science</title><imprint><date>2001</date></imprint><idno type="ISSN">0302-9743</idno><idno type="ISSN">0302-9743</idno></series><idno type="istex">11745BF5D1DA066A522379204279A822EB900FD9</idno><idno type="DOI">10.1007/3-540-45656-2_9</idno><idno type="ChapterID">9</idno><idno type="ChapterID">Chap9</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0302-9743</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Abstract: In this paper, we are proposing an efficient method of classifying form that is applicable in real life. Our method will identify a small number of local regions by their distinctive images with respect to their layout structure and then by using the DP (Dynamic Programming) matching to match only these local regions. The disparity score in each local region is defined and measured to select the matching regions. Genetic Algorithm will also be applied to select the best regions of matching from the viewpoint of a performance. Our approach of searching and matching only a small number of structurally distinctive local regions would reduce the processing time and yield a high rate of classification.</div></front></TEI><istex><corpusName>springer</corpusName><author><json:item><name>Yungcheol Byun</name><affiliations><json:string>Dept. of Computer Software Research Laboratory, ETRI, Korea</json:string><json:string>E-mail: bcart@csai.yonsei.ac.kr</json:string></affiliations></json:item><json:item><name>Sungsoo Yoon</name><affiliations><json:string>Dept. of Computer Science, Yonsei University, Korea</json:string></affiliations></json:item><json:item><name>Yeongwoo Choi</name><affiliations><json:string>Dept. of Computer Science, Sookmyung Women’s University, Korea</json:string></affiliations></json:item><json:item><name>Gyeonghwan Kim</name><affiliations><json:string>Dept. of Electronic Engineering, Sogang University, Korea</json:string></affiliations></json:item><json:item><name>Yillbyung Lee</name><affiliations><json:string>Dept. of Computer Science, Yonsei University, Korea</json:string></affiliations></json:item></author><language><json:string>eng</json:string></language><abstract>Abstract: In this paper, we are proposing an efficient method of classifying form that is applicable in real life. Our method will identify a small number of local regions by their distinctive images with respect to their layout structure and then by using the DP (Dynamic Programming) matching to match only these local regions. The disparity score in each local region is defined and measured to select the matching regions. Genetic Algorithm will also be applied to select the best regions of matching from the viewpoint of a performance. 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Robotics)</BookSubject><BookSubject Code="I16013" Priority="2" Type="Secondary">Computation by Abstract Devices</BookSubject><BookSubject Code="I16048" Priority="3" Type="Secondary">Mathematical Logic and Formal Languages</BookSubject><SubjectCollection Code="SUCO11645">Computer Science</SubjectCollection></BookSubjectGroup><BookContext><SeriesID>558</SeriesID></BookContext></BookInfo><BookHeader><EditorGroup><Editor AffiliationIDS="Aff1"><EditorName DisplayOrder="Western"><GivenName>Markus</GivenName><FamilyName>Stumptner</FamilyName></EditorName><Contact><Email>stumptner@cs.unisa.edu.au</Email></Contact></Editor><Editor AffiliationIDS="Aff1"><EditorName DisplayOrder="Western"><GivenName>Dan</GivenName><FamilyName>Corbett</FamilyName></EditorName><Contact><Email>corbett@cs.unisa.edu.au</Email></Contact></Editor><Editor AffiliationIDS="Aff2"><EditorName DisplayOrder="Western"><GivenName>Mike</GivenName><FamilyName>Brooks</FamilyName></EditorName><Contact><Email>mjb@cs.adelaide.edu.au</Email></Contact></Editor><Affiliation ID="Aff1"><OrgDivision>School of Computer and Information Science</OrgDivision><OrgName>University of South Australia</OrgName><OrgAddress><Street>Mawson Lakes</Street><Postcode>5095</Postcode><State>SA</State><Country>Australia</Country></OrgAddress></Affiliation><Affiliation ID="Aff2"><OrgDivision>Department of Computer Science</OrgDivision><OrgName>University of Adelaide</OrgName><OrgAddress><Postcode>5001</Postcode><City>Adelaide</City><State>SA</State><Country>Australia</Country></OrgAddress></Affiliation></EditorGroup></BookHeader><Part ID="Part1"><PartInfo TocLevels="0"><PartID>1</PartID><PartSequenceNumber>1</PartSequenceNumber><PartTitle>Papers</PartTitle><PartChapterCount>55</PartChapterCount><PartContext><SeriesID>558</SeriesID><BookID>3-540-45656-2</BookID><BookTitle>AI 2001: Advances in Artificial Intelligence</BookTitle></PartContext></PartInfo><Chapter ID="Chap9" Language="En"><ChapterInfo ChapterType="OriginalPaper" NumberingStyle="Unnumbered" Language="En" TocLevels="0" ContainsESM="No"><ChapterID>9</ChapterID><ChapterDOI>10.1007/3-540-45656-2_9</ChapterDOI><ChapterSequenceNumber>9</ChapterSequenceNumber><ChapterTitle Language="En">An Efficient Form Classification Method Using Partial Matching</ChapterTitle><ChapterFirstPage>95</ChapterFirstPage><ChapterLastPage>106</ChapterLastPage><ChapterCopyright><CopyrightHolderName>Springer-Verlag Berlin Heidelberg</CopyrightHolderName><CopyrightYear>2001</CopyrightYear></ChapterCopyright><ChapterHistory><RegistrationDate><Year>2002</Year><Month>2</Month><Day>13</Day></RegistrationDate><OnlineDate><Year>2002</Year><Month>2</Month><Day>14</Day></OnlineDate></ChapterHistory><ChapterGrants Type="Regular"><MetadataGrant Grant="OpenAccess"></MetadataGrant><AbstractGrant Grant="OpenAccess"></AbstractGrant><BodyPDFGrant Grant="Restricted"></BodyPDFGrant><BodyHTMLGrant Grant="Restricted"></BodyHTMLGrant><BibliographyGrant Grant="Restricted"></BibliographyGrant><ESMGrant Grant="Restricted"></ESMGrant></ChapterGrants><ChapterContext><SeriesID>558</SeriesID><PartID>1</PartID><BookID>3-540-45656-2</BookID><BookTitle>AI 2001: Advances in Artificial Intelligence</BookTitle></ChapterContext></ChapterInfo><ChapterHeader><AuthorGroup><Author AffiliationIDS="Aff5"><AuthorName DisplayOrder="Western"><GivenName>Yungcheol</GivenName><FamilyName>Byun</FamilyName></AuthorName><Contact><Email>bcart@csai.yonsei.ac.kr</Email></Contact></Author><Author AffiliationIDS="Aff6"><AuthorName DisplayOrder="Western"><GivenName>Sungsoo</GivenName><FamilyName>Yoon</FamilyName></AuthorName></Author><Author AffiliationIDS="Aff7"><AuthorName DisplayOrder="Western"><GivenName>Yeongwoo</GivenName><FamilyName>Choi</FamilyName></AuthorName></Author><Author AffiliationIDS="Aff8"><AuthorName DisplayOrder="Western"><GivenName>Gyeonghwan</GivenName><FamilyName>Kim</FamilyName></AuthorName></Author><Author AffiliationIDS="Aff6"><AuthorName DisplayOrder="Western"><GivenName>Yillbyung</GivenName><FamilyName>Lee</FamilyName></AuthorName></Author><Affiliation ID="Aff5"><OrgDivision>Dept. of Computer Software Research Laboratory</OrgDivision><OrgName>ETRI</OrgName><OrgAddress><Country>Korea</Country></OrgAddress></Affiliation><Affiliation ID="Aff6"><OrgDivision>Dept. of Computer Science</OrgDivision><OrgName>Yonsei University</OrgName><OrgAddress><Country>Korea</Country></OrgAddress></Affiliation><Affiliation ID="Aff7"><OrgDivision>Dept. of Computer Science</OrgDivision><OrgName>Sookmyung Women’s University</OrgName><OrgAddress><Country>Korea</Country></OrgAddress></Affiliation><Affiliation ID="Aff8"><OrgDivision>Dept. of Electronic Engineering</OrgDivision><OrgName>Sogang University</OrgName><OrgAddress><Country>Korea</Country></OrgAddress></Affiliation></AuthorGroup><Abstract ID="Abs1" Language="En"><Heading>Abstract</Heading><Para>In this paper, we are proposing an efficient method of classifying form that is applicable in real life. Our method will identify a small number of local regions by their distinctive images with respect to their layout structure and then by using the DP (Dynamic Programming) matching to match only these local regions. The disparity score in each local region is defined and measured to select the matching regions. Genetic Algorithm will also be applied to select the best regions of matching from the viewpoint of a performance. Our approach of searching and matching only a small number of structurally distinctive local regions would reduce the processing time and yield a high rate of classification.</Para></Abstract></ChapterHeader><NoBody></NoBody></Chapter></Part></Book><SubSeries><SubSeriesInfo><SubSeriesID>1244</SubSeriesID><SubSeriesTitle Language="En">Lecture Notes in Artificial Intelligence</SubSeriesTitle><SubSeriesSubTitle Language="En">Subseries of Lecture Notes in Computer Science</SubSeriesSubTitle></SubSeriesInfo><SubSeriesHeader><EditorGroup><Editor AffiliationIDS="Aff3"><EditorName DisplayOrder="Western"><GivenName>Jaime</GivenName><GivenName>G.</GivenName><FamilyName>Carbonell</FamilyName></EditorName></Editor><Editor AffiliationIDS="Aff4"><EditorName DisplayOrder="Western"><GivenName>Jörg</GivenName><FamilyName>Siekmann</FamilyName></EditorName></Editor><Affiliation ID="Aff3"><OrgName>Carnegie Mellon University</OrgName><OrgAddress><City>Pittsburgh</City><State>PA</State><Country>USA</Country></OrgAddress></Affiliation><Affiliation ID="Aff4"><OrgName>University of Saarland</OrgName><OrgAddress><City>Saarbrücken</City><Country>Germany</Country></OrgAddress></Affiliation></EditorGroup></SubSeriesHeader></SubSeries></Series></Publisher></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>An Efficient Form Classification Method Using Partial Matching</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>An Efficient Form Classification Method Using Partial Matching</title></titleInfo><name type="personal"><namePart type="given">Yungcheol</namePart><namePart type="family">Byun</namePart><affiliation>Dept. of Computer Software Research Laboratory, ETRI, Korea</affiliation><affiliation>E-mail: bcart@csai.yonsei.ac.kr</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Sungsoo</namePart><namePart type="family">Yoon</namePart><affiliation>Dept. of Computer Science, Yonsei University, Korea</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Yeongwoo</namePart><namePart type="family">Choi</namePart><affiliation>Dept. of Computer Science, Sookmyung Women’s University, Korea</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Gyeonghwan</namePart><namePart type="family">Kim</namePart><affiliation>Dept. of Electronic Engineering, Sogang University, Korea</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Yillbyung</namePart><namePart type="family">Lee</namePart><affiliation>Dept. of Computer Science, Yonsei University, Korea</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="conference [eBooks]" displayLabel="OriginalPaper"></genre><originInfo><publisher>Springer Berlin Heidelberg</publisher><place><placeTerm type="text">Berlin, Heidelberg</placeTerm></place><dateIssued encoding="w3cdtf">2001</dateIssued><copyrightDate encoding="w3cdtf">2001</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType></physicalDescription><abstract lang="en">Abstract: In this paper, we are proposing an efficient method of classifying form that is applicable in real life. Our method will identify a small number of local regions by their distinctive images with respect to their layout structure and then by using the DP (Dynamic Programming) matching to match only these local regions. The disparity score in each local region is defined and measured to select the matching regions. Genetic Algorithm will also be applied to select the best regions of matching from the viewpoint of a performance. Our approach of searching and matching only a small number of structurally distinctive local regions would reduce the processing time and yield a high rate of classification.</abstract><relatedItem type="host"><titleInfo><title>AI 2001: Advances in Artificial Intelligence</title><subTitle>14th Australian Joint Conference on Artificial Intelligence Adelaide, Australia, December 10–14, 2001 Proceedings</subTitle></titleInfo><name type="personal"><namePart type="given">Markus</namePart><namePart type="family">Stumptner</namePart><affiliation>School of Computer and Information Science, University of South Australia, Mawson Lakes, 5095, SA, Australia</affiliation><affiliation>E-mail: stumptner@cs.unisa.edu.au</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Dan</namePart><namePart type="family">Corbett</namePart><affiliation>School of Computer and Information Science, University of South Australia, Mawson Lakes, 5095, SA, Australia</affiliation><affiliation>E-mail: corbett@cs.unisa.edu.au</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Mike</namePart><namePart type="family">Brooks</namePart><affiliation>Department of Computer Science, University of Adelaide, 5001, Adelaide, SA, Australia</affiliation><affiliation>E-mail: mjb@cs.adelaide.edu.au</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><genre type="Book Series" displayLabel="Proceedings"></genre><originInfo><copyrightDate encoding="w3cdtf">2001</copyrightDate><issuance>monographic</issuance></originInfo><subject><genre>Book Subject Collection</genre><topic authority="SpringerSubjectCodes" authorityURI="SUCO11645">Computer Science</topic></subject><subject><genre>Book Subject Group</genre><topic authority="SpringerSubjectCodes" authorityURI="I">Computer Science</topic><topic authority="SpringerSubjectCodes" authorityURI="I21017">Artificial Intelligence (incl. 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