Now showing items 1-7 of 7

  • Aboutness from a commonsense perspective. 

    Bruza, Peter D.; Song, Dawei; Wong, Kam-Fai (Wiley, 2000-10)
    BRUZA, P. D., SONG, D. and WONG, K. F., 2000. Aboutness from a commonsense perspective. Journal of the American Society for Information Science and Technology (JASIST), 51 (12), pp. 1090- 1105.
    Information retrieval (IR) is driven by a process which decides whether a document is about a query. Recent attempts spawned from logic-based information retrieval theory have formalized properties characterizing ...
  • Application of aboutness to functional benchmarking in information retrieval. 

    Wong, Kam-Fai; Song, Dawei; Bruza, Peter D.; Cheng, Chin-Hung (ACM http://doi.acm.org/10.1145/502795.502796, 2001-10)
    WONG, K. F., SONG, D., BRUZA, P. D. and CHENG, C. H., 2001. Application of aboutness to functional benchmarking in information retrieval. ACM Transactions on Information Systems, 19 (4), pp. 337-370.
    Experimental approaches are widely employed to benchmark the performance of an information retrieval (IR) system. Measurements in terms of recall and precision are computed as performance indicators. Although they are ...
  • Back to the future: a logical framework for temporal information representation and inferencing from financial news. 

    Huang, Zi; Wong, Kam-Fai; Li, Wenjei; Song, Dawei; Bruza, Peter D. (IEEE, 2003-10)
    HUANG, Z., WONG, K-F., LI, W., SONG, D., and BRUZA, P. D., 2003. Back to the future: a logical framework for temporal information representation and inferencing from financial news. In: C. ZONG, ed. 2003 International Conference on Natural Language Processing and Knowledge Engineering: Proceedings. October 2003. IEEE Press. pp.95-101.
    Temporal information carries information about changes and time of the changes. Consider a company investing in another company. The former may choose to inject the money gradually with the amount and frequency depending ...
  • Commonsense aboutness for information retrieval. 

    Bruza, Peter D.; Song, Dawei; Wong, Kam-Fai; Cheng, Chin-Hung (IOS Press, 2000)
    BRUZA, P. D., SONG, D., WONG, K. F. and CHENG, C. H., 2000. Commonsense aboutness for information retrieval. In: M. MOHAMMADIAN, ed. Advances in Intelligent Systems: Theory and Applications. Amsterdam: IOS Press. pp. 288-295.
    Information retrieval (IR) is driven by a process which decides whether a document is about a query. Recent attempts have been made to formalize properties of “aboutness”, but no consensus has been reached. The properties ...
  • Comparing dissimilarity measures for content-based image retrieval. 

    Liu, Haiming; Song, Dawei; Ruger, Stefan; Hu, Rui; Uren, Victoria (Springer http://dx.doi.org/10.1007/978-3-540-68636-1_5, 2008)
    LIU, H., SONG, D., RUGER, S., HU, R. AND UREN, V., 2008. Comparing dissimilarity measures for content-based image retrieval. In: H. LI, T. LIU, W-Y. MA, T. SAKAI, K-F. WONG and G. ZHOU, eds. Information Retrieval Technology: 4th Asia Information Retrieval Symposium, AIRS 2008, Harbin, China, January 15-18, 2008; Revised Selected Papers. Berlin: Springer. pp. 44-50.
    Dissimilarity measurement plays a crucial role in contentbased image retrieval, where data objects and queries are represented as vectors in high-dimensional content feature spaces. Given the large number of dissimilarity ...
  • Fundamental properties of aboutness. 

    Bruza, Peter D.; Song, Dawei; Wong, Kam-Fai (ACM Press http://doi.acm.org/10.1145/312624.312696, 1999-08)
    BRUZA, P. D., SONG, D. and WONG, K. F., 1999. Fundamental properties of aboutness. In: Proceedings of the Twenty-Second Annual International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR99). 15-19 August 1999. New York: ACM Press. pp. 277-278.
  • An intelligent information agent for document title classification and filtering in document-intensive domains. 

    Song, Dawei; Lau, Raymond Y. K.; Bruza, Peter D.; Wong, Kam-Fai; Chen, Ding-Yi (Elsevier http://dx.doi.org/10.1016/j.dss.2007.04.001, 2007-11)
    SONG, D., LAU, R. Y. K., BRUZA, P. D., WONG, K. F. and CHEN, D. Y., 2007. An intelligent information agent for document title classification and filtering in document-intensive domains. Decision Support Systems, 44 (1), pp. 251-265.
    Effective decision making is based on accurate and timely information. However, human decision makers are often overwhelmed by the huge amount of electronic data these days. The main contribution of this paper is the ...