Advertisement

Query Generation Techniques for Patent Prior-Art Search in Multiple Languages

  • Dong Zhou
  • Jianxun Liu
  • Sanrong Zhang
Conference paper
  • 1.6k Downloads
Part of the Communications in Computer and Information Science book series (CCIS, volume 400)

Abstract

Patent prior-art search is an necessary step to ensure that no previous similar disclosures were made before granting an patent. The task is to identify all relevant information which may invalidate the originality of a claim of a patent application. Using the whole patent or extracting high indicative terms to form a query reduces the search burden on the user. To date, There are no large-scale experiments conducted specifically for evaluating query generation techniques used in patent prior-art search in multiple languages. In the following paper, we firstly introduced seven methods for generating patent queries for ranking. Then a large-scale experimental evaluation was carried out on the CLEF-IP 2009 multilingual dataset in English, French and German. A detail comparison of the different methods in terms of performance and efficiency has been performed in addition to the use of full-length documents as queries in the patent search. The results show that some methods, work well in information retrieval in general, fail to achieve the same effectiveness in the patent search. Different methods demonstrated distinct performance w.r.t query and document languages.

Keywords

Patent Prior-Art Search Multilingual Information Access Query Generation 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Tait, J. (ed.): Proceedings of the 1st ACM workshop on Patent Information Retrieval, PaIR 2008, Napa Valley, California, USA, October 30. ACM (2008)Google Scholar
  2. 2.
    Mahdabi, P., Andersson, L., Keikha, M., Crestani, F.: Automatic refinement of patent queries using concept importance predictors. In: Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2012, pp. 505–514. ACM, New York (2012)Google Scholar
  3. 3.
    Piroi, F., Lupu, M., Hanbury, A., Zenz, V.: Clef-ip 2011: Retrieval in the intellectual property domain. In: CLEF (Notebook Papers/Labs/Workshop) (2011)Google Scholar
  4. 4.
    Xue, X., Croft, W.B.: Transforming patents into prior-art queries. In: Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009, pp. 808–809. ACM, New York (2009)Google Scholar
  5. 5.
    Piroi, F.: Clef-ip 2010: Retrieval experiments in the intellectual property domain. In: CLEF (Notebook Papers/LABs/Workshops) (2010)Google Scholar
  6. 6.
    Mahdabi, P., Andersson, L., Hanbury, A., Crestani, F.: Report on the clef-ip 2011 experiments: Exploring patent summarization. In: CLEF (Notebook Papers/Labs/Workshop) (2011)Google Scholar
  7. 7.
    Becks, D., Eibl, M., Jürgens, J., Kürsten, J., Wilhelm, T., Womser-Hacker, C.: Does patent ir profit from linguistics or maximum query length? In: CLEF (Notebook Papers/Labs/Workshop) (2011)Google Scholar
  8. 8.
    Magdy, W., Jones, G.J.F.: Applying the kiss principle for the clef- ip 2010 prior art candidate patent search task. In: CLEF (Notebook Papers/LABs/Workshops) (2010)Google Scholar
  9. 9.
    Lopez, P., Romary, L.: Experiments with citation mining and key-term extraction for prior art search. In: CLEF (Notebook Papers/LABs/Workshops) (2010)Google Scholar
  10. 10.
    Zhou, D., Truran, M., Brailsford, T., Wade, V., Ashman, H.: Translation techniques in cross-language information retrieval. ACM Computing Surveys 45(1), 1:1–1:44 (2012)Google Scholar
  11. 11.
    Zhou, D., Truran, M., Brailsford, T., Ashman, H.: A hybrid technique for english-chinese cross language information retrieval. ACM Transactions on Asian Language Information Processing 7(2), 5:1–5:35 (2008)Google Scholar
  12. 12.
    Iwayama, M., Fujii, A., Kando, N., Takano, A.: Overview of patent retrieval task at ntcir-3. In: Proceedings of the ACL-2003 Workshop on Patent Corpus Processing, PATENT 2003, vol. 20, pp. 24–32. Association for Computational Linguistics, Stroudsburg (2003)CrossRefGoogle Scholar
  13. 13.
    Itoh, H., Mano, H., Ogawa, Y.: Term distillation in patent retrieval. In: Proceedings of the ACL-2003 Workshop on Patent Corpus Processing, PATENT 2003, vol. 20, pp. 41–45. Association for Computational Linguistics, Stroudsburg (2003)CrossRefGoogle Scholar
  14. 14.
    Magdy, W., Lopez, P., Jones, G.J.F.: Simple vs. Sophisticated approaches for patent prior-art search. In: Clough, P., Foley, C., Gurrin, C., Jones, G.J.F., Kraaij, W., Lee, H., Mudoch, V. (eds.) ECIR 2011. LNCS, vol. 6611, pp. 725–728. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  15. 15.
    Mahdabi, P., Keikha, M., Gerani, S., Landoni, M., Crestani, F.: Building queries for prior-art search. In: Hanbury, A., Rauber, A., de Vries, A.P. (eds.) IRFC 2011. LNCS, vol. 6653, pp. 3–15. Springer, Heidelberg (2011)Google Scholar
  16. 16.
    Ganguly, D., Leveling, J., Magdy, W., Jones, G.J.: Patent query reduction using pseudo relevance feedback. In: Proceedings of the 20th ACM International Conference on Information and Knowledge Management, CIKM 2011, pp. 1953–1956. ACM, New York (2011)Google Scholar
  17. 17.
    Mahdabi, P., Andersson, L., Hanbury, A., Crestani, F.: Report on the clef-ip 2011 experiments: Exploring patent summarization. In: CLEF (Notebook Papers/Labs/Workshop) (2011)Google Scholar
  18. 18.
    Porter, M.F.: Readings in information retrieval, pp. 313–316. Morgan Kaufmann Publishers Inc., San Francisco (1997)Google Scholar
  19. 19.
    Järvelin, K., Kekäläinen, J.: Ir evaluation methods for retrieving highly relevant documents. In: Proceedings of the 23rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2000, pp. 41–48. ACM, New York (2000)CrossRefGoogle Scholar
  20. 20.
    Ounis, I., Amati, G., Plachouras, V., He, B., Macdonald, C., Lioma, C.: Terrier: A High Performance and Scalable Information Retrieval Platform. In: Proceedings of ACM SIGIR 2006 Workshop on Open Source Information Retrieval, OSIR 2006 (August 2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Dong Zhou
    • 1
  • Jianxun Liu
    • 1
  • Sanrong Zhang
    • 1
  1. 1.Key Laboratory of Knowledge Processing and Networked Manufacturing &, School of Computer Science and EngineeringHunan University of Science and TechnologyXiangtanChina

Personalised recommendations