Characterizing Health-Related Information Needs of Domain Experts

Conference object English OPEN
Znaidi , Eya; Tamine , Lynda; Chouquet , Cécile; Latiri , Chira;
(2013)
  • Publisher: Springer-Verlag
  • Related identifiers: doi: 10.1007/978-3-642-38326-7_8
  • Subject: [ INFO.INFO-IT ] Computer Science [cs]/Information Theory [cs.IT] | Recherche d'information | Health information retrieval | [ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR] | [INFO.INFO-IT]Computer Science [cs]/Information Theory [cs.IT] | [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR] | Théorie de l'information | Statistical analysis | Information needs
International audience; In information retrieval literature, understanding the users’ intents behind the queries is critically important to gain a better insight of how to select relevant results. While many studies investigated how users in general carry out explorator... View more
  • References (23)
    23 references, page 1 of 3

    1. Andrews, J.E., Pearce, K.A., Ireson, C., Love, M.M.: Information-seeking behaviors of practitioners in a primary care practice-based research network (PBRN). Journal of the Medical Library Association, JMLA 93(2), 206-212 (2005)

    2. Arora, N., Hesse, B., Rimer, B.K., Viswanath, K., Clayman, M., Croyle, R.: Frustrated and confused: the american and public rates its cancer-related informationseeking experiences. Journal of General Internal Medicine 23(3), 223-228 (2007)

    3. Bhavnani, S.: Important cognitive components of domain-specific knowledge. In: Proceedings of Text Rerieval Conference TREC, TREC 2001, pp. 571-578 (2001)

    4. Bhavnani, S.: Domain specific strategies for the effective retrieval of health care and shopping information. In: Proceedings of SIGCHI, pp. 610-611 (2002)

    5. Boudin, F., Nie, J., Bartlett, J.C., Grad, R., Pluye, P., Dawes, M.: Combining classifiers for robust pico element detection. BMC Medical Informatics and Decision Making, 1-6 (2010)

    6. Dinh, D., Tamine, L.: Biomedical concept extraction based on combining the content-based and word order similarities. In: Proceedings of the 2011 ACM Symposium on Applied Computing, SAC 2011, pp. 1159-1163. ACM, New York (2011)

    7. Dinh, D., Tamine, L.: Combining Global and Local Semantic Contexts for Improving Biomedical Information Retrieval. In: Clough, P., Foley, C., Gurrin, C., Jones, G.J.F., Kraaij, W., Lee, H., Mudoch, V. (eds.) ECIR 2011. LNCS, vol. 6611, pp. 375-386. Springer, Heidelberg (2011)

    8. Dogan, R., Muray, G., N´ev´eol, A., Lu, Z.: Understanding pubmed user search behavior through log analysis. Database Journal, 1-19 (2009)

    9. Ely, J.W., Osheroff, J.A., Ebell, M.H., Chambliss, M.L., Vinson, D.C., Stevermer, J.J., Pifer, E.A.: Obstacles to answering doctors' questions about patient care with evidence: qualitative study. BMJ 324(7339), 710 (2002)

    10. Eysenbach, G.: Consumer health informatics. Biomedical Journal (3), 543-557 (2012)

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