Now showing items 6-11 of 11

  • Hybrid models for combination of visual and textual features in context-based image retrieval. 

    Kaliciak, Leszek (Robert Gordon University School of Computing Science and Digital Media, 2013-07)
    Visual Information Retrieval poses a challenge to intelligent information search systems. This is due to the semantic gap, the difference between human perception (information needs) and the machine representation of ...
  • Introspective knowledge acquisition for case retrieval networks in textual case base reasoning. 

    Chakraborti, Sutanu (Robert Gordon University School of Computing Science and Digital Media., 2007-08)
    Textual Case Based Reasoning (TCBR) aims at effective reuse of information contained in unstructured documents. The key advantage of TCBR over traditional Information Retrieval systems is its ability to incorporate ...
  • A knowledge acquisition tool to assist case authoring from texts. 

    Asiimwe, Stella Maris (The Robert Gordon University School of Computing, 2009-03)
    ASIIMWE, S., CRAW, S., WIRATUNGA, N. and TAYLOR, B. 2007. Automatically acquiring structured case representations: the SMART way. In: Applications and Innovations in Intelligent Systems XV: Proceedings of the 27th BCS SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence. Spirnger. pp. 45-49
     
    ASIIMWE, S., CRAW, S., WIRATUNGA, N. and TAYLOR, B. 2007. Automatic text standardisation by synonym mapping. In: Proceedings of the 12th UK Workshop on Case-Based Reasoning. CMS Press. pp. 88-98
     
    ASIIMWE, S., CRAW, S., TAYLOR, B. and WIRATUNGA, N. 2007. Case authoring: from textual reports to knowledge-rich cases. In: Proceedings of the 7th International Conference on Case-Based Reasoning. Springer. pp. 179-193
     
    ASIIMWE, S., CRAW, S. and TAYLOR, B. 2006. Discovering a concept hierarchy from Smart-House reports. In: Workshop Proceedings of the 8th European Conference on Case-Based Reasoning. pp. 88-97
     
    Case-Based Reasoning (CBR) is a technique in Artificial Intelligence where a new problem is solved by making use of the solution to a similar past problem situation. People naturally solve problems in this way, without ...
  • Learning adaptation knowledge to improve case-based reasoning 

    Craw, Susan; Wiratunga, Nirmalie; Rowe, Ray (Elsevier http://dx.doi.org/10.1016/j.artint.2006.09.001, 2006-11)
    CRAW, S., WIRATUNGA, N. and ROWE, R., 2006. Learning adaptation knowledge to improve case-based reasoning. Artificial Intelligence, 170 (16-17), pp. 1175-1192.
    Case-Based Reasoning systems retrieve and reuse solutions for previously solved problems that have been encountered and remembered as cases. In some domains, particularly where the problem solving is a classification task, ...
  • Representation and learning schemes for sentiment analysis. 

    Mukras, Rahman (The Robert Gordon University School of Computing, 2009-01)
    MUKRAS, R., WIRATUNGA, N., LOTHIAN, R., CHAKRABORTI, S. and HARPER, D., 2007. Information gain feature selection for ordinal text classification using probability redistribution. In: Proceedings of IJCAI Textlink Workshop.
     
    MUKRAS, R., WIRATUNGA, N. and LOTHIAN, R., 2007. Selecting bi-tags for sentiment analysis of text. In: Proceedings of AI-2007. Cambridge: Springer. pp. 181-194
     
    MUKRAS, R., WIRATUNGA, N. and LOTHIAN, R., 2007. The Robert Gordon University at the opinion retrieval task of the 2007 Trec blog track. In: Proceedings of TREC 2007.
     
    CHAKRABORTI, S., MUKRAS, R., LOTHIAN, R., WIRATUNGA, N., WATT, S. and HARPER, D., 2007. Supervised latent semantic indexing using adaptive sprinkling. In: Proceedings of IJCAI. AAAI Press. pp. 1582-1587.
     
    ORECCHIONI, A., WIRATUNGA, N., MASSIE, S., CHAKRABORTI, S. and MUKRAS, R., 2007. Learning incident causes. In: Proceedings of ICCBR TCBR Workshop, 2007.
     
    This thesis identifies four novel techniques of improving the performance of sentiment analysis of text systems. Thes include feature extraction and selection, enrichment of the document representation and exploitation ...
  • Role of semantic indexing for text classification. 

    Sani, Sadiq (Robert Gordon University School of Computing Science and Digital Media, 2014-09)
    The Vector Space Model (VSM) of text representation suffers a number of limitations for text classification. Firstly, the VSM is based on the Bag-Of-Words (BOW) assumption where terms from the indexing vocabulary are ...