Now showing items 4-8 of 8

  • Effective dependency rule-based aspect extraction for social recommender systems. 

    Chen, Yoke Yie; Wiratunga, Nirmalie; Lothian, Robert (ASSOCIATION FOR INFORMATION SYSTEMS http://aisel.aisnet.org/, 2017-07-16)
    CHEN, Y.Y., WIRATUNGA, N. and LOTHIAN, R. 2017. Effective dependency rule-based aspect extraction for social recommender systems. In Proceedings of the 21st Pacific Asia conference on information systems 2017 (PACIS 2017), 16-20 July 2017, Langkawi, Malaysia. (accepted).
    Social recommender systems capitalise on product reviews to generate recommendations that are both guided by experiential knowledge and are explained by user opinions centred on important product aspects. Therefore, having ...
  • 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)
    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 ...