An efficient method for using machine translation technologies in cross-language patent search

Walid Magdy, Gareth J F Jones

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

Topics in prior-art patent search are typically full patent applications and relevant items are patents often taken from sources in different languages. Cross language patent retrieval (CLPR) technologies support searching for relevant patents across multiple languages. As such, CLPR requires a translation process between topic and document languages. The most popular method for crossing the language barrier in cross language information retrieval (CLIR) in general is machine translation (MT). High quality MT systems are becoming widely available for many language pairs and generally have higher effectiveness for CLIR than dictionary based methods. However for patent search, using MT for translation of the very long search queries requires significant time and computational resources. We present a novel MT approach specifically designed for CLIR in general and CLPR in particular. In this method information retrieval (IR) text pre-processing in the form of stop word removal and stemming are applied to the MT training corpus prior to the training phase of the MT system. Applying this step leads to a significant decrease in the MT computational and resource requirements in both the training and translation phases. Experiments on the CLEF-IP 2010 CLPR task show the new technique to be 5 to 23 times faster than standard MT for query translation, while maintaining statistically indistinguishable IR effectiveness. Furthermore the new method is significantly better than standard MT when only limited translation training resources are available.

Original languageEnglish
Title of host publicationInternational Conference on Information and Knowledge Management, Proceedings
Pages1925-1928
Number of pages4
DOIs
Publication statusPublished - 13 Dec 2011
Externally publishedYes
Event20th ACM Conference on Information and Knowledge Management, CIKM'11 - Glasgow, United Kingdom
Duration: 24 Oct 201128 Oct 2011

Other

Other20th ACM Conference on Information and Knowledge Management, CIKM'11
CountryUnited Kingdom
CityGlasgow
Period24/10/1128/10/11

Fingerprint

Machine translation
Language
Patents
Patent retrieval
Resources
Cross-language information retrieval
Information retrieval
Query
Experiment
Language barriers
Art
Query translation

Keywords

  • cross-language information retrieval
  • machine translation
  • patent retrieval

ASJC Scopus subject areas

  • Business, Management and Accounting(all)
  • Decision Sciences(all)

Cite this

Magdy, W., & Jones, G. J. F. (2011). An efficient method for using machine translation technologies in cross-language patent search. In International Conference on Information and Knowledge Management, Proceedings (pp. 1925-1928) https://doi.org/10.1145/2063576.2063856

An efficient method for using machine translation technologies in cross-language patent search. / Magdy, Walid; Jones, Gareth J F.

International Conference on Information and Knowledge Management, Proceedings. 2011. p. 1925-1928.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Magdy, W & Jones, GJF 2011, An efficient method for using machine translation technologies in cross-language patent search. in International Conference on Information and Knowledge Management, Proceedings. pp. 1925-1928, 20th ACM Conference on Information and Knowledge Management, CIKM'11, Glasgow, United Kingdom, 24/10/11. https://doi.org/10.1145/2063576.2063856
Magdy W, Jones GJF. An efficient method for using machine translation technologies in cross-language patent search. In International Conference on Information and Knowledge Management, Proceedings. 2011. p. 1925-1928 https://doi.org/10.1145/2063576.2063856
Magdy, Walid ; Jones, Gareth J F. / An efficient method for using machine translation technologies in cross-language patent search. International Conference on Information and Knowledge Management, Proceedings. 2011. pp. 1925-1928
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