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Automatic detection of treatment relationships for patent retrieval
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Conference on Information and Knowledge Management archive
Proceeding of the 1st ACM workshop on Patent information retrieval table of contents
Napa Valley, California, USA
SESSION: Information extraction table of contents
Pages 9-14  
Year of Publication: 2008
ISBN:978-1-60558-256-6
Authors
Aaron Chu  UCLA, Los Angeles, CA, USA
Shigeyuki Sakurai  Japan Patent Office, Tokyo, Japan
Alfonso F. Cardenas  UCLA, Los Angeles, CA, USA
Sponsors
SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
SIGIR: ACM Special Interest Group on Information Retrieval
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

We devise a method for automatically detecting treatment relationships using lexico-syntactic patterns and its application to medical-oriented patent retrieval. This process for detecting treatment relationships involves finding lexico-syntactic patterns that are highly indicative of treatment relationships and also producing classification rules for those patterns.

This treatment relationship detection process is then used in a system to find treatment relationships based on a user query in a medical patent source. The query will consist of terms that the user wants to find in the subject or object of a treatment relationship. This is of great interest to both patent examiners and patent applicants as they search for prior art. Through the use of classification rules, this system was able to achieve a precision of 85.81% on a set of 20 test queries.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Aaron Chu: colleagues
Shigeyuki Sakurai: colleagues
Alfonso F. Cardenas: colleagues