A segmentation method for bibliographic references by contextual tagging of fields
Identifieur interne : 001659 ( Main/Exploration ); précédent : 001658; suivant : 001660A segmentation method for bibliographic references by contextual tagging of fields
Auteurs : Dominique Besagni [États-Unis] ; Abdel Belaïd [France] ; Nelly Benet [France]Source :
Descripteurs français
Abstract
In this paper, a method based on part of speech tagging (PoS) is used for bibliographic reference structure. This method operates on a roughly structured ASCII file, produced by OCR. Because of the heterogeneity of the reference structure, the method acts in a bottom up way, without an a priori model, gathering structural elements from basic tags to sub-fields and fields. Significant tags are first grouped in homogeneous classes according to their grammar categories and then reduced in canonical forms corresponding to record fields: ``authors'', title, conference name, date, etc. Non labelled tokens are integrated in one or another field by either applying PoS correction rules or using a structure model generated from well detected records. The designed prototype operates with a great satisfaction on different record layouts and character recognition qualities. Without manual intervention, 96.6% words are correctly attributed, and about 75,9% references are completely segmented from 2500 references.
Url:
Affiliations:
- France, États-Unis
- Lorraine
- Nancy
- Institut national polytechnique de Lorraine, Université Nancy 2, Université de Lorraine
Links toward previous steps (curation, corpus...)
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Le document en format XML
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This method operates on a roughly structured ASCII file, produced by OCR. Because of the heterogeneity of the reference structure, the method acts in a bottom up way, without an a priori model, gathering structural elements from basic tags to sub-fields and fields. Significant tags are first grouped in homogeneous classes according to their grammar categories and then reduced in canonical forms corresponding to record fields: ``authors'', title, conference name, date, etc. Non labelled tokens are integrated in one or another field by either applying PoS correction rules or using a structure model generated from well detected records. The designed prototype operates with a great satisfaction on different record layouts and character recognition qualities. Without manual intervention, 96.6% words are correctly attributed, and about 75,9% references are completely segmented from 2500 references.</div></front></TEI><affiliations><list><country><li>France</li><li>États-Unis</li></country><region><li>Lorraine</li></region><settlement><li>Nancy</li></settlement><orgName><li>Institut national polytechnique de Lorraine</li><li>Université Nancy 2</li><li>Université de Lorraine</li></orgName></list><tree><country name="États-Unis"><noRegion><name sortKey="Besagni, Dominique" sort="Besagni, Dominique" uniqKey="Besagni D" first="Dominique" last="Besagni">Dominique Besagni</name></noRegion></country><country name="France"><region name="Lorraine"><name sortKey="Belaid, Abdel" sort="Belaid, Abdel" uniqKey="Belaid A" first="Abdel" last="Belaïd">Abdel Belaïd</name></region><name sortKey="Benet, Nelly" sort="Benet, Nelly" uniqKey="Benet N" first="Nelly" last="Benet">Nelly Benet</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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