Abstract
In this paper, we propose a term identification system using conditional random fields (CRFs) on two biomedical datasets. Through employing several sets of experiments, we make a comprehensive investigation for different types of features. The final experimental results reflect that with carefully designed features i.e., adding not only the individual and dynamic features but also the combinational features, our system can identify biomedical terms with fairly high accuracy on both datasets, compared with other top systems already published in the literature.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Liu, F., Chen, Y., Manderick, B.: Named Entity Recognition in Biomedical Literature using Two-Layer Support Vector Machines. In: The 9th International conference on Enterprise Information Systems (ICEIS 2007), Funchal, Portugal, vol. AIDSS, pp. 39–45 (2007)
Klinger, R., Friedrich, C.M., Fluck, J., Hofmann-Apitius, M.: Named Entity Recognition with Combinations of Conditional Random Fields. In: The second BioCreAtIvE Challenge Workshop: Critical Assessment of Information Extractions in Molecular Biology, Madrid, Spain, pp. 89–91 (2007)
Humphreys, K., Demetriou, G., Gaizauskas, R.: Two Applications of Information Extraction to Biological Science Journal Articles: Enzyme Interactions and Protein Structures. In: The Pacific Symposium on Biocomputing, vol. 5, pp. 502–513 (2000)
Boeckmann, B., Bairoch, A., Apweiler, R., Blatter, M.C., Estreicher, A., Gasteiger, E., Martin, M.J., Michoud, K., O’Donovan, C., Phan, I., Pilbout, S., Schneider, M.: The SWISS-PROT Protein Knowledgebases and Its Supplement TeEMBL in 2003. Nucleic Acid Res. 31, D365–D370 (2003)
Entrez Gene Database, http://www.ncbi.nlm.nih.gov/sites/entrez?db=gene
Wain, H.M., et al.: Genew: the Human Gene Nomenclature Database, 2004 updates. Nucleic Acid Res. 32 (Database issue), D255–D257 (2004)
Kudo, T., Matsumoto, Y.: Chunking with Support Vector Machines. In: Second Meeting of North American Chapter of the Association for Computational Linguistics (NAACL), pp. 192–199 (2001)
Lafferty, J., McCallum, A., Pereira, F.: Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data. In: The Eighteenth International Conference on Machine Learning (ICML 2001) (2001)
CRF++: Yet Another CRF toolkit, http://crfpp.sourceforge.net/
The second Biocreative - Critical Assessment for Information Extraction in Biology Challenge, http://biocreative.sourceforge.net
Huang, H., Lin, Y., Lin, K., Kuo, C., Chang, Y., Yang, B., Chung, I., Hsu, C.: High-Recall Gene Mention Recognition by Unification of Multiple Backward Parsing Models. In: The Second BioCreAtIvE Challenge Workshop: Critical Assessment of Information Extraction in Molecular Biology, pp. 109–111 (2007)
Collier, N., Kim, J.: Introduction to the Bio-Entity Recognition Task at JNLPBA. In: COLING 2004 International Joint workshop on Natural Language Processing in Biomedicine and its Applications (NLPBA/BioNLP), pp. 73–78 (2004)
Chen, Y., Liu, F., Manderick, B.: Improving the Performance of Gene Mention Recognition System using Reformed Lexicon-based Support Vector Machine. In: The 2007 International Conference on Data Mining (DMIN 2007), Las Vegas, Nevada, pp. 228–234 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chen, Y., Liu, F., Manderick, B. (2008). Evaluating and Comparing Biomedical Term Identification Systems. In: Huang, DS., Wunsch, D.C., Levine, D.S., Jo, KH. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues. ICIC 2008. Lecture Notes in Computer Science, vol 5226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87442-3_119
Download citation
DOI: https://doi.org/10.1007/978-3-540-87442-3_119
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-87440-9
Online ISBN: 978-3-540-87442-3
eBook Packages: Computer ScienceComputer Science (R0)