Mariana L. Neves
ABSTRACT
The BioNLP'09 Shared Task on Event Extraction presented an evaluation on the extraction of biological events related to genes/proteins from the literature. We propose a system that uses the case-based reasoning (CBR) machine learning approach for the extraction of the entities (events, sites and location). The mapping of the proteins in the texts to the previously extracted entities is carried out by some simple manually developed rules for each of the arguments under consideration (cause, theme, site or location). We have achieved an f-measure of 24.15 and 21.15 for Task 1 and 2, respectively.
- Aamodt, A.,&Plaza, E. (1994). Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches. AI Communications, 7(1), 39--59. Google Scholar
Digital Library
- Chatr-aryamontri, A., Ceol, A., Palazzi, L. M., Nardelli, G., Schneider, M. V., Castagnoli, L., et al. (2007). MINT: the Molecular INTeraction database. Nucleic Acids Res, 35(Database issue), D572--574.Google Scholar
- Kerrien, S., Alam-Faruque, Y., Aranda, B., Bancarz, I., Bridge, A., Derow, C., et al. (2007). IntAct--open source resource for molecular interaction data. Nucleic Acids Res, 35(Database issue), D561--565.Google Scholar
- Kim, J.-D., Ohta, T., Pyysalo, S., Kano, Y.,&Tsujii, J. i. (2009). Overview of BioNLP'09 Shared Task on Event Extraction. Paper presented at the Proceedings of Natural Language Processing in Biomedicine (BioNLP) NAACL 2009 Workshop, Boulder, CO, USA. Google ScholarDigital Library
- Kim, J. D., Ohta, T.,&Tsujii, J. (2008). Corpus annotation for mining biomedical events from literature. BMC Bioinformatics, 9, 10.Google ScholarCross Ref
- Krallinger, M., Leitner, F., Rodriguez-Penagos, C.,&Valencia, A. (2008). Overview of the protein-protein interaction annotation extraction task of BioCreative II. Genome Biol, 9 Suppl 2, S4.Google ScholarCross Ref
- Neves, M., Chagoyen, M., Carazo, J. M.,&Pascual-Montano, A. (2008). CBR-Tagger: a case-based reasoning approach to the gene/protein mention problem. Paper presented at the Proceedings of the BioNLP 2008 Workshop at ACL 2008, Columbus, OH, USA. Google ScholarDigital Library
- Porter, M. (1980). An algorithm for suffix stripping. Program, 14(3), 130--137.Google ScholarCross Ref
- Pyysalo, S., Ginter, F., Heimonen, J., Bjorne, J., Boberg, J., Jarvinen, J., et al. (2007). BioInfer: a corpus for information extraction in the biomedical domain. BMC Bioinformatics, 8, 50.Google ScholarCross Ref
- Tsuruoka, Y., Tateishi, Y., Kim, J.-D., Ohta, T., McNaught, J., Ananiadou, S., et al. (2005). Developing a Robust Part-of-Speech Tagger for Biomedical Text. Paper presented at the Advances in Informatics - 10th Panhellenic Conference on Informatics. Google ScholarDigital Library
Index Terms
- Extraction of biomedical events using case-based reasoning
Recommendations
Biomedical events extraction using the hidden vector state model
Objective: Biomedical events extraction concerns about events describing changes on the state of bio-molecules from literature. Comparing to the protein-protein interactions (PPIs) extraction task which often only involves the extraction of binary ...
Disambiguating biomedical acronyms using EMIM
SIGIR '11: Proceedings of the 34th international ACM SIGIR conference on Research and development in Information RetrievalExpanding a query with acronyms or their corresponding 'long-forms' has not been shown to provide consistent improvements in the biomedical IR literature. The major open issue with expanding acronyms in a query is their inherent ambiguity, as an acronym ...
Comments