Semantic-based Knowledge Discovery in Biomedical Literature

Fatiha Boubekeur, Sabrina Cherdioui, Yassine Djouadi

2013

Abstract

Knowledge discovery in literature aims at searching for hidden and previously unknown knowledge within the published literature. Swanson’s discoveries on fish oil/Raynaud disease or migraine/magnesium connections from MEDLINE, an online bibliographic biomedical database, exemplify such discovery. In this paper, we present a novel approach for literature-based knowledge discovery that relies on the joint use of (1) flexible information retrieval techniques and (2) concepts’ semantic relatedness to discover hidden connections between MeSH concepts in the published biomedical scientific literature. The approach has been tested by replicating the Swanson's early discovery on fish oil/Raynaud disease connection. The obtained results show the effectiveness of our approach.

References

  1. Amati G., 2003. Probabilistic models for Information Retrieval based on Divergence from Randomness, PhD Thesis, University of Glasgow.
  2. Baziz M., Boughanem M., Aussenac-Gilles N., 2005. A Conceptual Indexing Approach for the TREC Robust Task. In The Fourteenth Text REtrieval Conference Proceedings (TREC 2005), Gaithersburg, Maryland, 15/11/2005-18/11/2005. E. M. Voorhees, Lori P. Buckland (Eds.), NIST, November 2005.
  3. Chen R., Lin H., Yang Z., 2011. Passage retrieval based hidden knowledge discovery from biomedical literature. Expert Systems with Applications, pp. 9958- 9964.
  4. Coletti M. H., and Bleich H. L., 2001. Medical subject headings used to search the biomedical literature. Journal of the American Medical Informatics Association, Vol. 8, pp. 317-323.
  5. Ganiz M. C., Pottenger W. M., Janneck C. D, 2005. Recent Advances in Literature Based Discovery. Journal of the American Society for Information Science and Technology, JASIS.
  6. Gordon M. D., Lindsay R. K., 1996. Towards discovery support systems: a replication, re-examination, and extension of Swanson's work on literature-based discovery of a connection between Raynaud's and fish oil. Journal of the American Society for Information Science, Vol. 47, p.116-128.
  7. Gordon M. D., Dumais S., 1998. Using Latent Semantic Indexing for literature based discovery. Journal of the American Society for Information Science and Technology, Vol. 49, p. 674-685.
  8. Gordon M. D., Lindsay R. K., 1999. Literature-based discovery by lexical statistics. Journal of the American Society for Information Science, Vol. 50, p.574-587.
  9. Hristovski D., Stare J., Peterlin B., Dzeroski S., 2001. Supporting discovery in medicine by association rule mining in MEDLINE and UMLS. Medinfo, Vol. 10, p. 1344-1348.
  10. Hu X., Zhang X., Yoo I., Zhou X., Xu X., 2010. Mining Hidden Connections among Biomedical Concepts from Disjoint Biomedical Literature Sets through Semantic-Based Association Rule. International Journal of Intelligent Systems, Vol. 25, Issue 2, (February 2010), pp. 207-223.
  11. Liu H., Le Pendu P., Ruoming Jin, Dejing Dou., 2011. A Hypergraph-based Method for Discovering Semantically Associated Itemsets. In Proceedings of the 2011 IEEE 11th International Conference on Data Mining (ICDM 7811). IEEE Computer Society, Washington, DC, USA, pp. 398-406.
  12. Liu X., Fu H., 2012. Literature-based knowledge discovery: the stat of the art. CoRR abs/1203.3611.
  13. Ponte J. M., Croft W. B. A Language Modeling Approach to Information Retrieval. In Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval, pp. 275-281
  14. Robertson S. E., Walker S., Hancock-Beaulieu M., 1998. Okapi at TREC-7: Automatic AdHoc, Filtering, VLC and Interactive. In Proceedings Text REtrieval Conference, TREC-7, p.199-210.
  15. Srinivasan P., 2004. Text Mining Generating Hypotheses from MEDLINE. Journal of the American Society for Information Science and Technology, Vol. 55, pp.396- 413.
  16. Stegmann J., Grohmann G., 2003. Hypothesis generation guided by co-word clustering. Scientometrics, Vol. 56 N°1, pp. 111-135.
  17. Swanson D. R., 1986a. Undiscovered public knowledge. Library Quarterly, Vol. 56, N°2, pp. 103-118.
  18. Swanson D. R., 1986b. Fish oil, Raynaud's syndrome, and undiscovered public knowledge. Perspectives in Biology and Medicine, Vol 30, p.7-18.
  19. Swanson D. R., 1988. Migraine and magnesium: eleven neglected connections. Perspectives in Biology and Medicine, Vol 31, pp. 526-557.
  20. Swanson D. R., 1989. Online search for logically-related noninteractive medical literature: A systematic trialand-error strategy. Journal of the American Society of Information Science, Vol. 40, pp. 356-358.
  21. Weeber M., Klein H., de Jong-van den Berg L. T. W. , 2001. Using concepts in literature-based discovery: Simulating Swanson's Raynaud - fish oil and Migraine - magnesium discoveries. Journal of the American Society for Information Science and Technology, Vol. 52, pp. 548-557.
  22. Wu Z., Palmer M., 1994.Verb semantics and Lexical selection. In Proceedings of the 32th Annual Meetings of the Association for Computational Linguistics, pp. 133-138.
Download


Paper Citation


in Harvard Style

Boubekeur F., Cherdioui S. and Djouadi Y. (2013). Semantic-based Knowledge Discovery in Biomedical Literature . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval and the International Conference on Knowledge Management and Information Sharing - Volume 1: KDIR, (IC3K 2013) ISBN 978-989-8565-75-4, pages 37-44. DOI: 10.5220/0004546300370044


in Bibtex Style

@conference{kdir13,
author={Fatiha Boubekeur and Sabrina Cherdioui and Yassine Djouadi},
title={Semantic-based Knowledge Discovery in Biomedical Literature},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval and the International Conference on Knowledge Management and Information Sharing - Volume 1: KDIR, (IC3K 2013)},
year={2013},
pages={37-44},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004546300370044},
isbn={978-989-8565-75-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval and the International Conference on Knowledge Management and Information Sharing - Volume 1: KDIR, (IC3K 2013)
TI - Semantic-based Knowledge Discovery in Biomedical Literature
SN - 978-989-8565-75-4
AU - Boubekeur F.
AU - Cherdioui S.
AU - Djouadi Y.
PY - 2013
SP - 37
EP - 44
DO - 10.5220/0004546300370044