Now showing items 7-12 of 12

  • 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)
    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)
    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 of ...
  • 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 ...