Skip to main content

Word Occurrence Based Extraction of Work Contributors from Statements of Responsibility

  • Conference paper
Research and Advanced Technology for Digital Libraries (TPDL 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8092))

Included in the following conference series:

Abstract

This paper addresses the identification of all contributors of an intellectual work, when they are recorded in bibliographic data but in unstructured form. National bibliographies are very reliable on representing the first author of a work, but frequently, secondary contributors are represented in the statements of responsibility that are transcribed by the cataloguer from the book into the bibliographic records. The identification of work contributors mentioned in statements of responsibility is a typical motivation for the application of information extraction techniques. This paper presents an approach developed for the specific application scenario of the ARROW rights infrastructure being deployed in several European countries to assist in the determination of the copyright status of works that may not be under public domain. Our approach performed reliably in most languages and bibliographic datasets of at least one million records, achieving precision and recall above 0.97 on five of the six evaluated datasets. We conclude that the approach can be reliably applied to other national bibliographies and languages.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Joint Steering Committee for Revision of AACR: Anglo-American Cataloguing Rules, 2nd edn. (2005) ISBN: 978-1-85604-570-4

    Google Scholar 

  2. Nadeau, D., Sekine, S.: A survey of named entity recognition and classification. Linguisticae Investigationes 30 (2007)

    Google Scholar 

  3. McCallum, A., Freitag, D., Pereira, F.: Maximum entropy Markov models for information extraction and segmentation. In: International Conference on Machine Learning (2000)

    Google Scholar 

  4. Martins, B., Borbinha, J., Pedrosa, G., Gil, J., Freire, N.: Geographically-aware information retrieval for collections of digitized historical maps. In: 4th ACM Workshop on Geographical information Retrieval (2007)

    Google Scholar 

  5. Freire, N., Borbinha, J., Calado, P., Martins, B.: A Metadata Geoparsing System for Place Name Recognition and Resolution in Metadata Records. In: ACM/IEEE Joint Conference on Digital Libraries (2011)

    Google Scholar 

  6. Sporleder, C.: Natural Language Processing for Cultural Heritage Domains. Language and Linguistics Compass 4(9), 750–768 (2010)

    Article  Google Scholar 

  7. King, P., Poulovassilis, A.: Enhancing database technology to better manage and exploit Partially Structured Data. Technical report, University of London (2000)

    Google Scholar 

  8. Michelson, M., Knoblock, C.: Creating Relational Data from Unstructured and Ungrammatical Data Sources. Journal of Articial Intelligence Research 31, 543–590 (2008)

    MATH  Google Scholar 

  9. Guo, J., Xu, G., Cheng, X., Li, H.: Named Entity Recognition in Query. In: 32nd Annual ACM SIGIR Conference (2009)

    Google Scholar 

  10. Du, J., Zhang, Z., Yan, J., Cui, Y., Chen, Z.: Using Search Session Context for Named Entity Recognition in Query. In: 33rd Annual ACM SIGIR Conference (2010)

    Google Scholar 

  11. Freire, N., Borbinha, J., Calado, P.: An approach for Named Entity Recognition in Poorly Structured Data. In: Simperl, E., Cimiano, P., Polleres, A., Corcho, O., Presutti, V. (eds.) ESWC 2012. LNCS, vol. 7295, pp. 718–732. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  12. The Unicode Consortium, Unicode Text Segmentation (2010), http://www.unicode.org/reports/tr29/

  13. Crocker, D., Overell, P.: Augmented BNF for Syntax Specifications: ABNF. RFC Editor (2008)

    Google Scholar 

  14. Sang, T.K., Erik, F.: Introduction to the CoNLL-2002 Shared Task: Language-Independent Named Entity Recognition. In: Proceedings Conference on Natural Language Learning (2002)

    Google Scholar 

  15. Sang, T.K., Erik, F., De Meulder, F.: Introduction to the CoNLL-2003 Shared Task: Language-Independent Named Entity Recognition. In: Proceedings Conference on Natural Language Learning (2003)

    Google Scholar 

  16. Grishman, R., Sundheim, B.: Message Understanding Conference - 6: A Brief History. In: Proceeding of the International Conference on Computational Linguistics (1996)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Freire, N. (2013). Word Occurrence Based Extraction of Work Contributors from Statements of Responsibility. In: Aalberg, T., Papatheodorou, C., Dobreva, M., Tsakonas, G., Farrugia, C.J. (eds) Research and Advanced Technology for Digital Libraries. TPDL 2013. Lecture Notes in Computer Science, vol 8092. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40501-3_17

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-40501-3_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40500-6

  • Online ISBN: 978-3-642-40501-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics