Abstract
Most digital information resources for readers of the medical library exist in the form of unstructured free text (journal papers). Therefore it has become the new direction of data mining research to extract keywords in the collection of medical literature and turn them into structured knowledge that is easily accessible and analyzable. MetaMap, a mapping tool from free text to the UMLS Metathesaurus developed by the U.S. National Library of Medicine, maps keywords to the normative UMLS thesaurus, and provides a rating for the mapping degree of every word. The present study extracts keywords from the English language literature of insulin-like growth factors 1 research, assigns weights to the keywords using the BM25F model, screens out groups of important keywords, carries out a cluster analysis of these keywords.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
LOD2 EU Deliverable 3.1.1 Knowledge Extraction Extraction from Structured Sources, http://static.lod2.eu/Deliverables/deliverable-3.1.1.pdf
Swanson, D.R.: Fish oil, Raynaud’s syndrome, and undiscovered public knowledge. Perspect. Biol. Med. 30(1), 7–18 (1986)
Jenssen, T.K., Laegreid, A., Komorowski, J., Hovig, E.: A literature network of human genes for high-throughput analysis of gene expression. Nat. Genet. 28(1), 21–28 (2001)
Pustejovsky, J., Castaño, J., Saurí, R., Rumshinsky, A., Zhang, J., Luo, W.: Medstract: creating large-scale information servers for biomedical libraries. In: Pustejovsky, J., Castaño, J., Saurí, R., Rumshinsky, A., Zhang, J., Luo Medstract, W. (eds.) BioMed 2002 Proceedings of the ACL 2002 Workshop on Natural Language Processing in the Biomedical Domain, vol. 3 (2002)
Fayyad, U., Piatetsky-Shapiro, G.: Knowledge Discovery and Data Mining: Towards a Unifying Framework. In: Proceedings of the Second International Conference on Knowledge Discovery and Data Mining. AAAI, Portland (1996)
Chen, C.: CiteSpace II: Detecting and Visualizing Emerging Trends and Transient Patterns in Scientific Literature. Journal of the American Society for Information Science and Technology 57(3), 359–377 (2006)
Aronson, A.R., Lang, F.M.: An overview of MetaMap: historical perspective and recent advances. Journal of the American Medical Informatics Association 17(3), 229–236 (2010)
Robertson, S.E., Walker, S.: Some simple effective approximations to the 2-Poisson model for probabilistic weighted retrieval. In: SIGIR 1994 Proceedings of the 17th Annual International ACM (1994)
梁立明,武夷山. 科学计量学:理论探索与案例研究. 北京: 科学出版社 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yin, S., Li, C., Zhou, Y., Huang, J. (2014). Detecting Hotspots in Insulin-Like Growth Factors 1 Research through MetaMap and Data Mining Technologies. In: Huang, Z., Liu, C., He, J., Huang, G. (eds) Web Information Systems Engineering – WISE 2013 Workshops. WISE 2013. Lecture Notes in Computer Science, vol 8182. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54370-8_31
Download citation
DOI: https://doi.org/10.1007/978-3-642-54370-8_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-54369-2
Online ISBN: 978-3-642-54370-8
eBook Packages: Computer ScienceComputer Science (R0)