Search for patents using treatment and causal relationships

International Conference on Information and Knowledge Management, Proceedings

Volumn , Issue , 2010, Pages 1-9

  Krishnan, Ashwathi ^a   Cardenas, Alfonso F ^a   Springer, Derek ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Causal relationships; Patent retrieval; Treatment relationships

Indexed keywords

CAUSAL RELATIONSHIPS; LARGE POPULATION; PATENT DOCUMENTS; PATENT RETRIEVAL; RELATIONSHIP EXTRACTION; TREATMENT RELATIONSHIPS;

INFORMATION RETRIEVAL; KNOWLEDGE MANAGEMENT;

PATENTS AND INVENTIONS;

EID: 78651292203     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1871888.1871890     Document Type: Conference Paper

References (13)

1. Girju, R. 2003. Automatic Detection of Causal Relations for Question Answering. In Proceedings of the 41st Annual Meeting of the Association for Computational Linguistics (ACL 2003), Workshop on "Multilingual Summarization and Question Answering - Machine Learning and Beyond". 2003.
2. Banko, M. and Etzioni, O. 2008. The Tradeoffs Between Open and Traditional Relation Extraction. In Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics (ACL 2008).
3. Pantel, P. and Pennacchiotti, M. 2006. Espresso: Leveraging Generic Patterns for Automatically Harvesting Semantic Relations. In Proceedings of Conference on Computational Linguistics / Association for Computational Linguistics (COLING/ACL - 06), pp. 113-120. Sydney, Australia.
4. Chu, A., Sakurai, S. and Cárdenas, A. F. 2008. Automatic detection of treatment relationships for patent retrieval. In Proceeding of the 1st ACM workshop on Patent information retrieval, October 30, Napa Valley, California, USA.
5. Ravichandran, D. and Hovy, E. H. 2002. Learning surface text patterns for a question answering system. In Proceedings of ACL-2002, pp. 41-47. Philadelphia, PA.
6. A. Yates and O. Etzioni. 2007. Unsupervised resolution of objects and relations on the web. In Procs of NAACL/HLT.
7. The Penn Treebank project. http://www.cis.upenn.edu/~treebank/.
8. Larkey, L. 1999. A patent search and classification system. International Conference on Digital Libraries archive, In Proceedings of the fourth ACM conference on Digital libraries table of contents, Berkeley, California, United States, Pages: 179-187.
9. Larkey, L., Connell, M. and Callan, J. 2000. Collection selection and results merging with topically organized U.S. patents and TREC data. In Proceedings of the 9th International Conference on Information and Knowledge Management (CIKM), ACM, Pages: 282-289.
10. Wu, T., Holzman, L. E., Pottenger, W. M., Phelps, D. J. 2003. A Supervised Learning Algorithm for Information Extraction from Textual Data. In Proceedings of the workshop on Text Mining, Third SIAM International Conference on Data Mining.
11. Wanner, L., Baeza-Yates, R., Brügmann, S., Codina, J., Diallo, B., Escorsa, E., Giereth, M., Kompatsiaris, Y., Papadopoulos, S., Pianta, E., Piella, G., Puhlmann, I., Rao, G., Rotard, M., Schoester, P., Serafini, L., Zervaki, V. 2008. Towards Content-Oriented Patent Document Processing. World Patent Information, Elsevier, Vol. 30(1), Page: 21-33.
12. Tiwari, A. and Bansal, V. 2004. PATSEEK: Content Based Image Retrieval System for Patent Database. In Proceedings of the International Conference on Electronic Business ICEB, pages 1167-1171.
13. Vrochidis, S., Papadopoulos, S., Moumtzidou, A., Sidiropoulos, P., Pianta, E. and Kompatsiaris, I. 2010. Towards Content-based Patent Image Retrieval; A Framework Perspective. World Patent Information Journal, Volume 32, Issue 2, pp 94-106.