Recent Submissions

  • A scalable expressive ensemble learning using random prism: a mapreduce approach. 

    Stahl, Frederic; May, David; Mills, Hugo; Bramer, Max; Gaber, Mohamed Medhat (Springer Verlag Berlin Heidelberg http://dx.doi.org/10.1007/978-3-662-46703-9_4, 2015-03)
    STAHL, F., MAY, D., MILLS, H., BRAMER, M., and GABER, M., 2015. A scalable expressive ensemble learning using random prism: a mapreduce approach. In: A. HAMEURLEING, J. KING, R. WAGNER, S.SAKR, L. WANG and A. SOMAYA, eds. Transactions on large-scale data- and knowledge-centered systems XX: special issue on advanced techniques for big data management. Pp. 90-107.
    The induction of classification rules from previously unseen examples is one of the most important data mining tasks in science as well as commercial applications. In order to reduce the infl uence of noise in the ...
  • Twitter response to televised political debates in Election 2015. 

    Pedersen, Sarah; Baxter, Graeme; Burnett, Simon M.; MacLeod, Iain; Goker, Ayse; Heron, Michael; Isaacs, John; Elyan, Eyad; Kaliciak, Leszek (Centre for the Study of Journalism, Culture and Community, Bournemouth University. http://www.electionanalysis.uk/, 2015)
    PEDERSEN, S., BAXTER, G., BURNETT, S., MACLEOD, I., GOKER, A., HERON, M., ISAACS, J., ELYAN, E. and KALICIAK, L., 2015. Twitter response to televised political debates in Election 2015. In: D. JACKSON and E. THORSEN, eds. UK Election Analysis 2015: Media, Voters and the Campaign; Early reflections from leading UK academics. Bournemouth: Centre for the Study of Journalism, Culture and Community, Bournemouth University. p. 73.
  • 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 ...
  • 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 ...
  • 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 ...
  • 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 ...
  • 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 ...
  • 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 ...
  • Privacy through security: policy and practice in a small-medium enterprise. 

    Allison, Ian K.; Strangwick, Craig (IRM Press, 2008)
    ALLISON, I. and STRANGWICK, C., 2008. Privacy through security: policy and practice in a small-medium enterprise. In: R. SUBRAMANIAN, ED. Computer security, privacy, and politics: current issues, challenges, and solutions. Hershey, PA: IRM Press. pp. 157-179.
    The chapter discusses how one small business planned for, and implemented, the security of its data in a new enterprise-wide system. The company’s data was perceived as sensitive, and any breach of privacy as commercially ...
  • Concept induction via fuzzy C-means clustering in a high dimensional semantic space. 

    Song, Dawei; Cao, Guihong; Bruza, Peter D.; Lau, Raymond Y. K. (Wiley., 2007)
    SONG, D., CAO, G., BRUZA, P.D. and LAU, R. Y. K., 2007. Concept induction via fuzzy C-means clustering in a high dimensional semantic space. In: J. VALENTE DE OLIVEIRA and W. PEDRYCZ, eds. Advances in fuzzy clustering and its applications. Chichester: Wiley. Pp. 393-403.
    Lexical semantic space models have recently been investigated to automatically derive the meaning (semantics) of information based on natural language usage. In a semantic space, a term can be considered as a concept ...

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