Now showing items 1-5 of 5

  • Exploiting semantic association to answer ‘vague queries’. 

    Zhu, Jianhan; Eisenstadt, Marc; Song, Dawei; Denham, Chris (IOS Press, 2006)
    ZHU, J., EISENSTADT, M., SONG, D. and DENHAM, C. 2006. Exploiting semantic association to answer ‘vague queries’. In: Y. LI, M. LOOI and N. ZHONG, eds. Advances in Intelligent IT – Active Media Technology 2006: Volume 138 (Frontiers in Artificial Intelligence and Applications). Fairfax, VA: IOS Press. pp. 73-78
    Although today’s web search engines are very powerful, they still fail to provide intuitively relevant results for many types of queries, especially ones that are vaguely-formed in the user’s own mind. We argue that ...
  • Facilitating query decomposition in query language modeling by association rule mining using multiple sliding windows. 

    Song, Dawei; Huang, Qiang; Ruger, Stefan; Bruza, Peter D. (Springer http://dx.doi.org/10.1007/978-3-540-786-7_31, 2008)
    SONG, D., HUANG, Q., RUGER, S. and BRUZA, P. D., 2008. Facilitating query decomposition in query language modeling by association rule mining using multiple sliding windows. In: C. MACDONALD, I. OUNIS, V. PLACHOURAS, I. RUTHVEN and R.W. WHITE, eds. Advances in Information Retrieval: 30th European Conference on IR Research, ECIR 2008, Glasgow, UK, March 30-April 3, 2008; Proceedings. Berlin: Springer. pp. 334-345.
    This paper presents a novel framework to further advance the recent trend of using query decomposition and high-order term re- lationships in query language modeling, which takes into account terms implicitly associated ...
  • Integrating multiple windows and document features for expert finding. 

    Zhu, Jianhan; Song, Dawei; Ruger, Stefan (Wiley http://dx.doi.org/10.1002/asi.21012, 2009-04)
    ZHU, J, SONG, D. and RUGER, S., 2009. Integrating multiple windows and document features for expert finding. Journal of the American Society for Information Science and Technology, 60 (4), pp. 694-715.
    Expert finding is a key task in enterprise search and has recently attracted lots of attention from both research and industry communities. Given a search topic, a prominent existing approach is to apply some information ...
  • Query expansion using term relationships in language models for information retrieval. 

    Bai, Jing; Song, Dawei; Bruza, Peter D.; Nie, Jian-Yun; Cao, Guihong (ACM Press http://doi.acm.org/10.1145/1099554.1099725, 2005-11)
    BAI, J., SONG, D., BRUZA, P. D., NIE, J. Y. and CAO, G., 2005. Query expansion using term relationships in language models for information retrieval. In: A. CHOWDHURY, N. FUHR, M. RONTHALER, H.-J. SCHEK and W. TEIKEN, eds. Proceedings of the 14th ACM International Conference on Information and Knowledge Management. 31 October – 5 November 2005. New York : ACM Press. pp. 688-695.
    Language Modeling (LM) has been successfully applied to Information Retrieval (IR). However, most of the existing LM approaches only rely on term occurrences in documents, queries and document collections. In traditional ...
  • Robust query-specific pseudo feedback document selection for query expansion. 

    Huang, Qiang; Song, Dawei; Ruger, Stefan (Springer http://dx.doi.org/10.1007/978-3-540-78646-7_54, 2008)
    HUANG, Q., SONG, D. and RUGER, S., 2008. Robust query-specific pseudo feedback document selection for query expansion. In: C. MACDONALD, I. OUNIS, V. PLACHOURAS, I. RUTHVEN and R.W. WHITE, eds. Advances in Information Retrieval: 30th European Conference on IR Research, ECIR 2008, Glasgow, UK, March 30-April 3, 2008; Proceedings. Berlin: Springer. pp. 547- 554
    In document retrieval using pseudo relevance feedback, after initial ranking, a fixed number of top-ranked documents are selected as feedback to build a new expansion query model. However, very little at- tention has ...