Duplicate bibliographic record detection with an OCR-converted source of information
Identifieur interne : 000200 ( Main/Exploration ); précédent : 000199; suivant : 000201Duplicate bibliographic record detection with an OCR-converted source of information
Auteurs : Shoichi Taniguchi [Japon]Source :
- Journal of information science [ 0165-5515 ] ; 2013.
Descripteurs français
- Pascal (Inist)
- Wicri :
- topic : Bibliothèque, Catalogue.
English descriptors
- KwdEn :
Abstract
Duplicate record detection has been an important issue in the fields of data and records management and various detection methods have been proposed. A new method, which uses an optical character recognition (OCR)-converted source of information for record matching to detect duplicates, is proposed and examined in this paper. First, the design of an experiment for examining the perfor- mance of such a duplicate detection method is discussed. The base record set with an OCR-converted title page and its verso were prepared along with two test record sets from different union catalogues, and duplicate records between the base record set and the test sets were manually identified. A duplicate detection system was developed to execute matching (I) between records, (2) between a record and an OCR-converted source of information and (3) using a combination of these. Second, matching performance at the individual data element level is examined. Third, the performance of duplicate record detection based on matching at the element level is examined through rule-based detection and machine learning-based detection. The results of the experiment show the usefulness of incorporating source of information into duplicate detection to a certain extent.
Affiliations:
Links toward previous steps (curation, corpus...)
- to stream PascalFrancis, to step Corpus: 000047
- to stream PascalFrancis, to step Corpus: 000072
- to stream PascalFrancis, to step Curation: 000721
- to stream PascalFrancis, to step Checkpoint: 000043
- to stream Main, to step Merge: 000203
- to stream Main, to step Curation: 000200
Le document en format XML
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<author><name sortKey="Taniguchi, Shoichi" sort="Taniguchi, Shoichi" uniqKey="Taniguchi S" first="Shoichi" last="Taniguchi">Shoichi Taniguchi</name>
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<s3>JPN</s3>
<sZ>1 aut.</sZ>
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<country>Japon</country>
<wicri:noRegion>School of Library and Information Science, Keio University</wicri:noRegion>
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<author><name sortKey="Taniguchi, Shoichi" sort="Taniguchi, Shoichi" uniqKey="Taniguchi S" first="Shoichi" last="Taniguchi">Shoichi Taniguchi</name>
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<series><title level="j" type="main">Journal of information science</title>
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<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Bibliographic reference</term>
<term>Catalogs</term>
<term>Detection</term>
<term>Information source</term>
<term>Library</term>
<term>Optical character recognition</term>
<term>Title</term>
</keywords>
<keywords scheme="Pascal" xml:lang="fr"><term>Référence bibliographique</term>
<term>Détection</term>
<term>Reconnaissance optique caractère</term>
<term>Source information</term>
<term>Bibliothèque</term>
<term>Catalogue</term>
<term>Titre</term>
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<front><div type="abstract" xml:lang="en">Duplicate record detection has been an important issue in the fields of data and records management and various detection methods have been proposed. A new method, which uses an optical character recognition (OCR)-converted source of information for record matching to detect duplicates, is proposed and examined in this paper. First, the design of an experiment for examining the perfor- mance of such a duplicate detection method is discussed. The base record set with an OCR-converted title page and its verso were prepared along with two test record sets from different union catalogues, and duplicate records between the base record set and the test sets were manually identified. A duplicate detection system was developed to execute matching (I) between records, (2) between a record and an OCR-converted source of information and (3) using a combination of these. Second, matching performance at the individual data element level is examined. Third, the performance of duplicate record detection based on matching at the element level is examined through rule-based detection and machine learning-based detection. The results of the experiment show the usefulness of incorporating source of information into duplicate detection to a certain extent.</div>
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