Crf-based authors' name tagging for scanned documents

ABSTRACT

Authors' names are a critical bibliographic element when searching or browsing academic articles stored in digital libraries. Therefore, those creating metadata for digital libraries would appreciate an automatic method to extract such bibliographic data from printed documents. In this paper, we describe an automatic author name tagger for academic articles scanned with optical character recognition (OCR) mark-up. The method uses conditional random fields (CRF) for labeling the unsegmented character strings in authors' blocks as those of either an author or a delimiter. We applied the tagger to Japanese academic articles. The results of the experiments showed that it correctly labeled more than 99% of the author name strings, which compares favorably with the under 96% correct rate of our previous tagger based on a hidden Markov model (HMM).

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.7 DOCUMENT AND TEXT PROCESSING
      I.7.5 Document Capture
          Subjects: Optical character recognition (OCR)

Additional Classification:
  I. Computing Methodologies
  I.7 DOCUMENT AND TEXT PROCESSING
      I.7.5 Document Capture
          Subjects: Document analysis

General Terms:
Design, Experimentation

Keywords:
conditional random fields (crf), digital libraries, information extraction