Case-Based Reasoning for Invoice Analysis and Recognition
Identifieur interne : 000948 ( Istex/Corpus ); précédent : 000947; suivant : 000949Case-Based Reasoning for Invoice Analysis and Recognition
Auteurs : Hatem Hamza ; Yolande Belaïd ; Abdel BelaïdSource :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2007.
Abstract
Abstract: This paper introduces the approach CBRDIA (Case-based Reasoning for Document Invoice Analysis) which uses the principles of case-based reasoning to analyze, recognize and interpret invoices. Two CBR cycles are performed sequentially in CBRDIA. The first one consists in checking whether a similar document has already been processed, which makes the interpretation of the current one easy. The second cycle works if the first one fails. It processes the document by analyzing and interpreting its structuring elements (adresses, amounts, tables, etc) one by one. The CBR cycles allow processing documents from both knonwn or unknown classes. Applied on 923 invoices, CBRDIA reaches a recognition rate of 85,22% for documents of known classes and 74,90% for documents of unknown classes.
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DOI: 10.1007/978-3-540-74141-1_28
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Two CBR cycles are performed sequentially in CBRDIA. The first one consists in checking whether a similar document has already been processed, which makes the interpretation of the current one easy. The second cycle works if the first one fails. It processes the document by analyzing and interpreting its structuring elements (adresses, amounts, tables, etc) one by one. The CBR cycles allow processing documents from both knonwn or unknown classes. Applied on 923 invoices, CBRDIA reaches a recognition rate of 85,22% for documents of known classes and 74,90% for documents of unknown classes.</div></front></TEI><istex><corpusName>springer</corpusName><author><json:item><name>Hatem Hamza</name><affiliations><json:string>ITESOFT, Parc d’Andron, Le Sequoia. 30470 Aimargues., France</json:string><json:string>University Nancy 2, LORIA. 54506 Vandoeuvre-les-Nancy, France</json:string><json:string>E-mail: hamza@loria.fr</json:string></affiliations></json:item><json:item><name>Yolande Belaïd</name><affiliations><json:string>University Nancy 2, LORIA. 54506 Vandoeuvre-les-Nancy, France</json:string><json:string>E-mail: ybelaid@loria.fr</json:string></affiliations></json:item><json:item><name>Abdel Belaïd</name><affiliations><json:string>University Nancy 2, LORIA. 54506 Vandoeuvre-les-Nancy, France</json:string><json:string>E-mail: abelaid@loria.fr</json:string></affiliations></json:item></author><language><json:string>eng</json:string></language><abstract>Abstract: This paper introduces the approach CBRDIA (Case-based Reasoning for Document Invoice Analysis) which uses the principles of case-based reasoning to analyze, recognize and interpret invoices. 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Two CBR cycles are performed sequentially in CBRDIA. The first one consists in checking whether a similar document has already been processed, which makes the interpretation of the current one easy. The second cycle works if the first one fails. It processes the document by analyzing and interpreting its structuring elements (adresses, amounts, tables, etc) one by one. The CBR cycles allow processing documents from both knonwn or unknown classes. Applied on 923 invoices, CBRDIA reaches a recognition rate of 85,22% for documents of known classes and 74,90% for documents of unknown classes.</Para></Abstract><KeywordGroup Language="En"><Heading>Keywords</Heading><Keyword>Case-based reasoning</Keyword><Keyword>document case</Keyword><Keyword>structure case</Keyword><Keyword>invoice analysis</Keyword><Keyword>invoice interpretation</Keyword><Keyword>structure extraction</Keyword></KeywordGroup></ChapterHeader><NoBody></NoBody></Chapter></Part></Book></Series></Publisher></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>Case-Based Reasoning for Invoice Analysis and Recognition</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>Case-Based Reasoning for Invoice Analysis and Recognition</title></titleInfo><name type="personal"><namePart type="given">Hatem</namePart><namePart type="family">Hamza</namePart><affiliation>ITESOFT, Parc d’Andron, Le Sequoia. 30470 Aimargues., France</affiliation><affiliation>University Nancy 2, LORIA. 54506 Vandoeuvre-les-Nancy, France</affiliation><affiliation>E-mail: hamza@loria.fr</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Yolande</namePart><namePart type="family">Belaïd</namePart><affiliation>University Nancy 2, LORIA. 54506 Vandoeuvre-les-Nancy, France</affiliation><affiliation>E-mail: ybelaid@loria.fr</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Abdel</namePart><namePart type="family">Belaïd</namePart><affiliation>University Nancy 2, LORIA. 54506 Vandoeuvre-les-Nancy, France</affiliation><affiliation>E-mail: abelaid@loria.fr</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">2007</dateIssued><copyrightDate encoding="w3cdtf">2007</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: This paper introduces the approach CBRDIA (Case-based Reasoning for Document Invoice Analysis) which uses the principles of case-based reasoning to analyze, recognize and interpret invoices. Two CBR cycles are performed sequentially in CBRDIA. The first one consists in checking whether a similar document has already been processed, which makes the interpretation of the current one easy. The second cycle works if the first one fails. It processes the document by analyzing and interpreting its structuring elements (adresses, amounts, tables, etc) one by one. The CBR cycles allow processing documents from both knonwn or unknown classes. Applied on 923 invoices, CBRDIA reaches a recognition rate of 85,22% for documents of known classes and 74,90% for documents of unknown classes.</abstract><relatedItem type="host"><titleInfo><title>Case-Based Reasoning Research and Development</title><subTitle>7th International Conference on Case-Based Reasoning, ICCBR 2007 Belfast, Northern Ireland, UK, August 13-16, 2007 Proceedings</subTitle></titleInfo><name type="personal"><namePart type="given">Rosina</namePart><namePart type="given">O.</namePart><namePart type="family">Weber</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Michael</namePart><namePart type="given">M.</namePart><namePart type="family">Richter</namePart><role><roleTerm type="text">editor</roleTerm></role></name><genre type="Book Series" displayLabel="Proceedings"></genre><originInfo><copyrightDate encoding="w3cdtf">2007</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. Robotics)</topic><topic authority="SpringerSubjectCodes" authorityURI="I16048">Mathematical Logic and Formal Languages</topic><topic authority="SpringerSubjectCodes" authorityURI="W26007">Business Information Systems</topic></subject><identifier type="DOI">10.1007/978-3-540-74141-1</identifier><identifier type="ISBN">978-3-540-74138-1</identifier><identifier type="eISBN">978-3-540-74141-1</identifier><identifier type="ISSN">0302-9743</identifier><identifier type="eISSN">1611-3349</identifier><identifier type="BookTitleID">151831</identifier><identifier type="BookID">978-3-540-74141-1</identifier><identifier type="BookChapterCount">36</identifier><identifier type="BookVolumeNumber">4626</identifier><identifier type="BookSequenceNumber">4626</identifier><identifier type="PartChapterCount">10</identifier><part><date>2007</date><detail type="part"><title>Application Papers</title></detail><detail type="volume"><number>4626</number><caption>vol.</caption></detail><extent 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