Now showing items 1-2 of 2

  • Document re-ranking by generality in bio-medical information retrieval. 

    Yan, Xin; Li, Xue; Song, Dawei (Springer http://dx.doi.org/10.1007/11581062_28, 2005)
    YAN, X., LI, X. and SONG, D., 2005. Document re-ranking by generality in bio-medical information retrieval. In: A. NGU, M. KITSUREGAWA, E. NEUHOLD, J.-Y. CHUNG and Q. SHENG. Eds. Web Information Systems Engineering – WISE 2005: 6th International Conference on Web Information Systems Engineering, New York, NY, USA, November 20-22, 2005; Proceedings. Berlin: Springer. pp. 376-389.
    Document ranking is well known to be a crucial process in information retrieval (IR). It presents retrieved documents in an order of their estimated degrees of relevance to query. Traditional document rank- ing methods ...
  • LRD: latent relation discovery for vector space expansion and information retrieval. 

    Goncalves, Alexandre L.; Zhu, Jianhan; Song, Dawei; Uren, Victoria; Pacheco, Roberto (Springer http://dx.doi.org/10.1007/11775300_11, 2006)
    GONCALVES, A., ZHU, J., SONG, D., UREN, V. and PACHECO, R., 2006. LRD: latent relation discovery for vector space expansion and information retrieval. In: J. YU, M. KITSUREGAWA and H. LEONG, eds. Advances in Web-Age Information Management: 7th International Conference, WAIM 2006, Hong Kong, China, June 17-19, 2006; Proceedings. Berlin: Springer. pp. 122-133.
    In this paper, we propose a text mining method called LRD (latent relation discovery), which extends the traditional vector space model of docu-ment representation in order to improve information retrieval (IR) on docu-ments ...