Skip to main content

Mining, Ranking, and Using Acronym Patterns

  • Conference paper
Book cover Progress in WWW Research and Development (APWeb 2008)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4976))

Included in the following conference series:

Abstract

Techniques for being able to automatically identify acronym patterns are very important for enhancing a multitude of applications that rely upon search. This task is challenging, due to the many ways that acronyms and their expansions can be embedded in text. Methods for ranking and exploiting acronym patterns are another related, yet mostly untouched area. In this paper we present a new and extensible approach to discover acronym patterns. Furthermore, we present a new approach that can also be used for both ranking the patterns, as well as utilizing them within search queries. In our pattern discovery system, we are able to achieve a clear separation between higher and lower level functionalities. This enables great flexibility and allows users to easily configure and tune the system for different target domains. We evaluate our system and show how it is able to offer new capabilities, compared to existing work in the area.

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 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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. Brin, S.: Extracting Patterns and Relations from the World Wide Web. In: WebDB, pp. 172–183 (1998)

    Google Scholar 

  2. Chang, J.T., Schütze, H., Altman, R.B.: Creating an Online Dictionary of Abbreviations from MEDLINE. Journal of the American Medical Informatics Association 9, 612–620 (2003)

    Article  Google Scholar 

  3. Hawking, D., Craswell, N., Bailey, P., Griffihs, K.: Measuring Search Engine Quality. Information Retrieval 4(1), 33–59 (2001)

    Article  MATH  Google Scholar 

  4. Pustejovsky, J., Castano, J., Kotecki, M., Morrell, M.: Automatic Extraction of Acronym-Meaning Pairs from Medline Databases. Medinfo 10, 371–375 (2001)

    Google Scholar 

  5. Järvelin, K., Kekäläinen, J.: IR evaluation methods for retrieving highly relevant documents. SIGIR, 41–48 (2000)

    Google Scholar 

  6. Larkey, L.S., Ogilvie, P., Price, M.A., Tamilio, B.: Acrophile: An Automated Acronym Extractor and Server. ACM DL, 205–214 (2000)

    Google Scholar 

  7. Vladimir, I.: Levenshtein: Binary Codes Capable of Correcting Deletions, Insertions and Reversals. Doklady Akademii Nauk SSSR 163(4), 845–848 (1965)

    Google Scholar 

  8. Rimer, M., O’Connell, M.: BioABACUS: A Database of Abbreviations and Acronyms in Biotechnology and Computer Science. Bioinformatics 14(10), 888–889 (1998)

    Article  Google Scholar 

  9. Schwartz, A.S., Hearst, M.A.: A Simple Algorithm for Identifying Abbreviation Definitions in Biomedical Texts. In: Pacific Symposium on Biocomputing (2003)

    Google Scholar 

  10. Taghva, K., Gilbreth, J.: Recognizing Acronyms and Their Definitions. IJDAR 1(4), 191–198 (1999)

    Article  Google Scholar 

  11. Jonathan, D., Wren, H.R.: Garner: Heuristics for Identification of Acronym-Definition Patterns Within Text: Toward an Automated Construction of Comprehensive Acronym-Definition Dictionaries. Methods of Information in Medicine 41(5), 426–434 (2002)

    Google Scholar 

  12. Xu, J., Huang, Y.: Using SVM to Extract Acronyms from Text. Soft Comput. 11(4), 369–373 (2007)

    Article  Google Scholar 

  13. Baeza-Yates, R.A., Berthier, A.: Ribeiro-Neto: Modern Information Retrieval. ACM Press, New York (1999)

    Google Scholar 

  14. Yeates, S.: Automatic Extraction of Acronyms from Text. In: New Zealand Computer Science Research Students Conference, pp. 117–124 (1999)

    Google Scholar 

  15. Yi, J., Sundaresan, N.: Mining the Web for Acronyms Using the Duality of Patterns and Relations. In: Workshop on Web Information and Data Management, pp. 48–52 (1999)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Yanchun Zhang Ge Yu Elisa Bertino Guandong Xu

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Ji, X., Xu, G., Bailey, J., Li, H. (2008). Mining, Ranking, and Using Acronym Patterns. In: Zhang, Y., Yu, G., Bertino, E., Xu, G. (eds) Progress in WWW Research and Development. APWeb 2008. Lecture Notes in Computer Science, vol 4976. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78849-2_38

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-78849-2_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-78848-5

  • Online ISBN: 978-3-540-78849-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics