This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Third ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL'03)
Bibliographic Attribute Extraction from Erroneous References Based on a Statistical Model
Houston, Texas USA
May 27-May 31
ISBN: 0-7695-1939-3
Atsuhiro Takasu, National Institute of Informatics
In this paper, we propose a method for extracting bibliographic attributes from reference strings captured using Optical Character Recognition (OCR) and an extended hidden Markov model. Bibliographic attribute extraction can be used in two ways. One is reference parsing in which attribute values are extracted from OCR-processed references for bibliographic matching. The other is reference alignment in which attribute values are aligned to the bibliographic record to enrich the vocabulary of the bibliographic database. In this paper, we first propose a statistical model for attribute extraction that represents both the syntactical structure of references and OCR error patterns. Then, we perform experiments using bibliographic references obtained from scanned images of papers in journals and transactions and show that useful attribute values are extracted from OCR-processed references. We also show that the proposed model has advantages in reducing the cost of preparing training data, a critical problem in rule-based systems.
Citation:
Atsuhiro Takasu, "Bibliographic Attribute Extraction from Erroneous References Based on a Statistical Model," jcdl, pp.49, Third ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL'03), 2003
Usage of this product signifies your acceptance of the Terms of Use.