Now showing items 1-6 of 6

  • Case reuse in textual case-based reasoning. 

    Adeyanju, Ibrahim Adepoju (Robert Gordon University School of Computing, 2011-08)
    Text reuse involves reasoning with textual solutions of previous problems to solve new similar problems. It is an integral part of textual case-based reasoning (TCBR), which applies the CBR problem-solving methodology ...
  • Contextual sentiment analysis for social media genres. 

    Muhammad, Aminu; Wiratunga, Nirmalie; Lothian, Robert (Elsevier http://dx.doi.org/10.1016/j.knosys.2016.05.032, 2016-05-16)
    MUHAMMAD, A., WIRATUNGA, N. and LOTHIAN, R. 2016. Contextual sentiment analysis for social media genres. Knowledge-based systems [online], Articles in Press. Available from: http://dx.doi.org/10.1016/j.knosys.2016.05.032
    The lexicon-based approaches to opinion mining involve the extraction of term polarities from sentiment lexicons and the aggregation of such scores to predict the overall sentiment of a piece of text. It is typically ...
  • 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 ...
  • Related scientific information: a study on user-defined relevance. 

    Beresi, Ulises Cervino (Robert Gordon University School of Computing, 2011-09)
    This dissertation presents an investigation into the manifestations of relevance observed in the context of related scientific information. The main motivation is to observe if researchers, in the context of knowledge ...
  • 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 ...