Document recognition for a Digital Library
Identifieur interne : 000B88 ( Istex/Corpus ); précédent : 000B87; suivant : 000B89Document recognition for a Digital Library
Auteurs : N. Srihari ; W. Lam ; J. HullSource :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 1995.
Abstract
Abstract: Our work concerns three major processes which help to build a DL database for IR. Several components of the system are shown to be useful for creating a DL database. The design of these processes stresses the importance of robustness and ease of adaptation to the processing of different documents. Output generated by these processes facilitates the IR mechanism to produce intelligent response to user queries. An adaptive approach to document understanding was presented in this chapter. Its robustness was shown to be crucial to the success in processing varied library documents. This chapter also presented an adaptation of the vector space model for information retrieval to improving the performance of a word recognition algorithm. The neighborhoods of visually similar words determined by word recognition are matched to a database of documents and a subset of documents with topics that are similar to those of the input image are determined.
Url:
DOI: 10.1007/BFb0026853
Links to Exploration step
ISTEX:7133932DAB9E25F7D661F69E71FA4085686E2629Le document en format XML
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Recognition (CEDAR)</OrgDivision><OrgName>State University of New York at Buffalo</OrgName><OrgAddress><Street>520 Lee Entrance, Suite 202</Street><Postcode>14228</Postcode><City>Amherst</City><State>NY</State><Country>USA</Country></OrgAddress></Affiliation><Affiliation ID="Aff2"><OrgDivision>Center of Excellence for Document Analysis and Recognition (CEDAR)</OrgDivision><OrgName>State University of New York at Buffalo</OrgName><OrgAddress><Street>520 Lee Entrance, Suite 202</Street><Postcode>14228</Postcode><City>Amherst</City><State>NY</State><Country>USA</Country></OrgAddress></Affiliation><Affiliation ID="Aff3"><OrgDivision>Center of Excellence for Document Analysis and Recognition (CEDAR)</OrgDivision><OrgName>State University of New York at Buffalo</OrgName><OrgAddress><Street>520 Lee Entrance, Suite 202</Street><Postcode>14228</Postcode><City>Amherst</City><State>NY</State><Country>USA</Country></OrgAddress></Affiliation></AuthorGroup><Abstract ID="Abs1" Language="En"><Heading>Abstract</Heading><Para>Our work concerns three major processes which help to build a DL database for IR. Several components of the system are shown to be useful for creating a DL database. The design of these processes stresses the importance of robustness and ease of adaptation to the processing of different documents. Output generated by these processes facilitates the IR mechanism to produce intelligent response to user queries. An adaptive approach to document understanding was presented in this chapter. Its robustness was shown to be crucial to the success in processing varied library documents. This chapter also presented an adaptation of the vector space model for information retrieval to improving the performance of a word recognition algorithm. The neighborhoods of visually similar words determined by word recognition are matched to a database of documents and a subset of documents with topics that are similar to those of the input image are determined.</Para></Abstract></ChapterHeader><NoBody></NoBody></Chapter></Book></Series></Publisher></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>Document recognition for a Digital Library</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>Document recognition for a Digital Library</title></titleInfo><name type="personal"><namePart type="given">Sargur</namePart><namePart type="given">N.</namePart><namePart type="family">Srihari</namePart><affiliation>Center of Excellence for Document Analysis and Recognition (CEDAR), State University of New York at Buffalo, 520 Lee Entrance, Suite 202, 14228, Amherst, NY, USA</affiliation><affiliation>E-mail: srihari@cedar.buffalo.edu</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Stephen</namePart><namePart type="given">W.</namePart><namePart type="family">Lam</namePart><affiliation>Center of Excellence for Document Analysis and Recognition (CEDAR), State University of New York at Buffalo, 520 Lee Entrance, Suite 202, 14228, Amherst, NY, USA</affiliation><affiliation>E-mail: lam@cedar.buffalo.edu</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Jonathan</namePart><namePart type="given">J.</namePart><namePart type="family">Hull</namePart><affiliation>Center of Excellence for Document Analysis and Recognition (CEDAR), State University of New York at Buffalo, 520 Lee Entrance, Suite 202, 14228, Amherst, NY, USA</affiliation><affiliation>E-mail: hull@cedar.buffalo.edu</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="conference [eBooks]" displayLabel="ReviewPaper"></genre><originInfo><publisher>Springer Berlin Heidelberg</publisher><place><placeTerm type="text">Berlin, Heidelberg</placeTerm></place><dateIssued encoding="w3cdtf">1995</dateIssued><copyrightDate encoding="w3cdtf">1995</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: Our work concerns three major processes which help to build a DL database for IR. Several components of the system are shown to be useful for creating a DL database. The design of these processes stresses the importance of robustness and ease of adaptation to the processing of different documents. Output generated by these processes facilitates the IR mechanism to produce intelligent response to user queries. An adaptive approach to document understanding was presented in this chapter. Its robustness was shown to be crucial to the success in processing varied library documents. This chapter also presented an adaptation of the vector space model for information retrieval to improving the performance of a word recognition algorithm. The neighborhoods of visually similar words determined by word recognition are matched to a database of documents and a subset of documents with topics that are similar to those of the input image are determined.</abstract><relatedItem type="host"><titleInfo><title>Digital Libraries Current Issues</title><subTitle>Digital Libraries Workshop DL '94 Newark, NJ, USA, May 19–20, 1994 Selected Papers</subTitle></titleInfo><name type="personal"><namePart type="given">Nabil</namePart><namePart type="given">R.</namePart><namePart type="family">Adam</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Bharat</namePart><namePart type="given">K.</namePart><namePart type="family">Bhargava</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Yelena</namePart><namePart type="family">Yesha</namePart><role><roleTerm type="text">editor</roleTerm></role></name><genre type="Book Series" displayLabel="Proceedings"></genre><originInfo><copyrightDate encoding="w3cdtf">1995</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="I18024">Database Management</topic><topic authority="SpringerSubjectCodes" authorityURI="I18032">Information Storage and Retrieval</topic><topic authority="SpringerSubjectCodes" authorityURI="I18040">Information Systems Applications (incl.Internet)</topic><topic authority="SpringerSubjectCodes" authorityURI="I13022">Computer Communication Networks</topic><topic authority="SpringerSubjectCodes" authorityURI="I15041">Coding and Information Theory</topic><topic authority="SpringerSubjectCodes" authorityURI="I22021">Image Processing and Computer Vision</topic></subject><identifier type="DOI">10.1007/BFb0026845</identifier><identifier type="ISBN">978-3-540-59282-2</identifier><identifier type="eISBN">978-3-540-49230-6</identifier><identifier type="ISSN">0302-9743</identifier><identifier type="eISSN">1611-3349</identifier><identifier type="BookTitleID">42673</identifier><identifier type="BookID">3540592822</identifier><identifier type="BookChapterCount">17</identifier><identifier type="BookVolumeNumber">916</identifier><part><date>1995</date><detail type="volume"><number>916</number><caption>vol.</caption></detail><detail type="chapter"><number>8</number></detail><extent unit="pages"><start>119</start><end>128</end></extent></part><recordInfo><recordOrigin>Springer-Verlag, 1995</recordOrigin></recordInfo></relatedItem><relatedItem type="series"><titleInfo><title>Lecture Notes in Computer Science</title></titleInfo><name type="personal"><namePart type="given">Gerhard</namePart><namePart type="family">Goos</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Juris</namePart><namePart type="family">Hartmanis</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Jan</namePart><namePart type="family">van Leeuwen</namePart><role><roleTerm type="text">editor</roleTerm></role></name><originInfo><copyrightDate encoding="w3cdtf">1995</copyrightDate><issuance>serial</issuance></originInfo><identifier type="ISSN">0302-9743</identifier><identifier type="eISSN">1611-3349</identifier><identifier type="SeriesID">558</identifier><part><detail type="chapter"><number>8</number></detail></part><recordInfo><recordOrigin>Springer-Verlag, 1995</recordOrigin></recordInfo></relatedItem><identifier type="istex">7133932DAB9E25F7D661F69E71FA4085686E2629</identifier><identifier type="DOI">10.1007/BFb0026853</identifier><identifier type="ChapterID">8</identifier><identifier type="ChapterID">Chap8</identifier><accessCondition type="use and reproduction" contentType="copyright">Springer-Verlag, 1995</accessCondition><recordInfo><recordContentSource>SPRINGER</recordContentSource><recordOrigin>Springer-Verlag, 1995</recordOrigin></recordInfo></mods></metadata><enrichments></enrichments></istex></record>Pour manipuler ce document sous Unix (Dilib)
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