KXtractor: An effective biomedical information extraction technique based on mixture hidden markov models

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3680 LNBI, Issue , 2005, Pages 68-81

  Song, Min ^a   Song, Il Yeol ^a   Hu, Xiaohua ^a   Allen, Robert B ^a  

^a Drexel University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

INFORMATION EXTRACTION; KXTRACTOR; MIXTURE HIDDEN MARKOV MODELS; PART-OF-SPEECH;

BIOMEDICAL ENGINEERING; HTML; MARKOV PROCESSES; PROTEINS; TEXT PROCESSING;

INFORMATION RETRIEVAL;

EID: 33646187984     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11567752_5     Document Type: Conference Paper

References (20)

1. Blaschke, C., Andrade, M.A., Ouzounis, C., and Valencia, A. (1999). Automatic Extraction of Biological Information from Scientific Text: Protein-Protein Interactions, In Proceedings of the Seventh International Conference on Intelligent Systems for Molecular Biology, Heidelberg, Germany, 60-67.
2. Bunescu, R., Ge, R., Kate, R.J., Marcotte, E.M., Mooney, R.J., Ramani, A.K., and Wong, Y.W. (2004). Comparative Experiments on Learning Information Extractors for Proteins and their Interactions. To appear in Journal Artificial Intelligence in Medicine (Special Issue on Summarization and Information Extraction from Medical Documents).
3. Califf, M.E. and Mooney, R.J. (1999). Relational Learning of Pattern-Match Rules for Information Extraction. Proceedings of the Sixteenth National Conference on Artificial Intelligence (AAAI-99), Orlando, FL, 328-334.
4. Collier, N., Nobata,C., and Tsujii, J. (2000). Extracting the Names of Genes and Gene Products with a Hidden Markov Model. Proceedings of the 18th International Conference on Computational Linguistics (COLING2000), Saarbrucken, Germany, 201-207.
5. Cortes, C. and Vapnik, V. (1995). Support-Vector Networks. Machine Learning, 20(3): 273-297.
6. Freitag, D. and McCallum, A. (1999). Information extraction with HMMs and shrinkage. AAAI-99 Workshop on Machine Learning for Information Extraction, Orlando, FL, 31-36.
7. Friedman, C., Kra, P., Yu, H.,Krauthammer, M., and Rzhetsky, A. (2001). GENIES: a natural-language processing system for the extraction of molecular pathways from journal articles. Bioinformatics, 17 Suppl 1, S74-82.
8. Fukuda, K., Tamura, A., Tsunoda, T., and Takagi, T. (1998). Toward information extraction: identifying protein names from biological papers. Pacific Symposium Biocomputing. 707-18.
9. Jenssen, T.K., Laegreid, A., Komorowski, J., and Hovig, E. (2001). A literature network of human genes for high-throughput analysis of gene expression. Nature Genetics, 28(1): 21-8.
10. Krauthammer, M., Kra, P., Iossifov,I., Gomez, S. M., and Hripcsak, G. (2002). Of truth and pathways: Chasing bits of information through myriads of articles. Bioinformatics, 18 Suppl 1, S249-S257.
11. Kudo, T. and Matsumoto, Y. (2000). Use of Support Vector Learning for Chunk Identification. In Proceedings of CoNLL- 2000 and LLL-2000, Saarbruncken, Germany, 142-144.
12. Leek, T. R. (1997). Information extraction using Hidden Markov Models. MSc Thesis, Department of Computer Science, University of California, San Diego.
13. National Library of Medicine (2003). The MEDLINE database, http://www.mcbi.nlm.nih.gov/PubMed/.
14. Proux, D., Rechenmann, F., and Julliard, L. (2000). A pragmatic information extraction strategy for gathering data on genetic interactions. Proceedings of International Conference on Intelligent System for Molecular Biology, La Jolla, CA, 8:279-85.
15. Pustejovsky, J., Castano, J., Zhang, J., Kotecki, M., and Cochran, B. (2002). Robust relational parsing over biomedical literature: extracting inhibit relations. Pacific Symposium on Biocomputing, 362-73.
16. Rabiner, L. R. (1989). A Tutorial on Hidden Markov Models and selected applications in speech recognition. Proceedings of the IEEE, 77:257-286.
17. Shatkay H. and Feldman R. (2003). Mining the biomedical literature in the genomic era: An overview. Journal of Computational Biology, 10 (6): 821-855.
18. Skounakis, M., Craven, M., and Ray, S. (2003). Hierarchical Hidden Markov Models for Information Extraction. Proceedings of the 18th International Joint Conference on Artificial Intelligence, Acapulco, Mexico, August, 427-433.
19. Song, M, Song, I-Y., and Hu, X. (2003). KPSpotter: A Flexible Information Gain-based Keyphrase Extraction System, Fifth International Workshop on Web Information and Data Management (WIDM'03), New Orleans, LA, 50-53.
20. Viterbi, A. J. (1967). Error bounds for convolutional codes and an asymptotically optimal decoding algorithm. IEEE Transactions on Information Processing, 13:260-269.