Browsing School of Computer Science and Statistics by Author "BAYOMI, MOSTAFA MOHAMED"

Now showing items 1-3 of 3

    • C-HTS: A Concept-based Hierarchical Text Segmentation Approach 

      Lawless, Seamus; BAYOMI, MOSTAFA MOHAMED (2018)
      Hierarchical Text Segmentation is the task of building a hierarchical structure out of text to reflect its sub-topic hierarchy. Current text segmentation approaches are based upon using lexical and/or syntactic similarity ...

    • Towards Evaluating the Impact of Anaphora Resolution on Text Summarisation from a Human Perspective 

      BAYOMI, MOSTAFA MOHAMED; LEVACHER, KILLIAN; LAWLESS, SEAMUS; LAVIN, PETER; Ghorab, M. Rami; O’Connor, Alexander (Springer International Publishing, 2016)
      Automatic Text Summarisation (TS) is the process of abstracting key content from information sources. Previous research attempted to combine diverse NLP techniques to improve the quality of the produced summaries. ...

    • Using NLP Techniques to Enhance Content Discoverability and Reusability for Adaptive Systems 

      BAYOMI, MOSTAFA MOHAMED (Trinity College Dublin. School of Computer Science & Statistics. Discipline of Computer Science, 2019)
      The volume of digital content resources written as text documents is growing every day, at an unprecedented rate. Because this content is generally not structured as easy-to-handle units, it can be very difficult for users ...