A Biomedical Information Retrieval System based on Clustering for Mobile Devices

  1. Millán, Manuel
  2. Muñoz, Alejandro
  3. Villa Cordero, Manuel de la
  4. Maña López, Manuel Jesús
Journal:
Procesamiento del lenguaje natural

ISSN: 1135-5948

Year of publication: 2010

Issue: 45

Pages: 255-258

Type: Article

More publications in: Procesamiento del lenguaje natural

Abstract

Information overload caused by the increasing availability of online texts and publications of interest is a problem that increases when such information is necessary for decision making, as in the biomedical field. It is in this domain where we present an information retrieval system for mobile devices. Traditional indexing and search processes are enriched with the feature of returning the results in clusters according to their content.

Bibliographic References

  • Buenaga, M. de, Gachet, D., Maña, M., de la Villa, M., Mata J.:Clustering and Summarizing Medical Documents to Improve Mobile Retrieval. Workshop on Mobile Information Retrieval (MobIR’08) Singapore (2008)
  • Dempster, A.P., Laird, N.M., Rubin, D.B.: Maximum Likelihood from Incomplete Data via the EM Algorithm. Journal of the Royal Statistical Society. Series B (Methodological) 39 (1): 1–38 (1977)
  • Dunlavy, D.M., O'Leary, D.P., Conroy, J.M., Schlesinger, J.D. QCS: A system for querying, clustering and summarizing documents. Information Processing and Management 43(6), 1588--1605 (2007)
  • Garritty, C., El Emam, K.: Who's using PDAs? Estimates of PDA use by health care providers: a systematic review of surveys. J. of Medical Internet Research 8(2), e7 (2006)
  • Gospodnetic, O., Hatcher E., McCandless M.: Lucene in Action (2nd ed.). Manning Publications (2009)
  • Hauser, S.E., Demner-Fushman, D. et al.: Using Wireless Handheld Computers to Seek Information at the Point of Care: An Evaluation by Clinicians. Journal of the American Medical Informatics Association; Nov-Dec; 14(6): 807-15 (2007)
  • Hearst, M., Pedersen, P.: Reexamining the Cluster Hypothesis: Scatter/Gather on Retrieval Results. In: 19th Annual International ACM SIGIR Conference, pp. 76--84 (1996)
  • León, S.A., Fontelo, P., Green, L., Ackerman, M., Liu, F.: Evidence-based medicine among internal medicine residents in a community hospital program using smart phones. BMC Medical Informatics and Decision Making 7(5) (2007)
  • MacQueen, J. B.: Some Methods for classification and Analysis of Multivariate Observations. Proceedings of 5th Berkeley Symposium on Mathematical Statistics and Probability. University of California Press. pp. 281–297 (1966)
  • Maña, M.J., Buenaga, M., Gómez, J.M.: Multidocument summarization: An added value to clustering in interactive retrieval. ACM TOIS 22(2), 215--241 (2004)
  • Muñoz, M.A., Rodríguez, M., Favela, J., Martínez-García, A.I., González, V.M.: Context-aware mobile communication in hospitals. IEEE Computer 36(8), 38-46 (2003)
  • Rasmussen, E.: Clustering algorithms. En W. Frakes y R. Baeza-Yates, eds., Information Retrieval: Data Structures & Algorithms, pags. 419-442. Prentice-Hall International, London (1992)
  • Witten, I. H. y Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques (2nd ed.). Morgan Kaufmann, San Francisco. CA (2005)
  • W3C: Mobile Web Best Practices 1.0, Basic Guidelines. W3C Recommendation 29 July 2008. http://www.w3.org/TR/2008/RECmobile- bp-20080729/ (2008)