Leap2Trend: A Temporal Word Embedding Approach for Instant Detection of Emerging Scientific Trends

Amna Dridi*, Mohamed Medhat Gaber, R. Muhammad Atif Azad, Jagdev Bhogal

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    21 Citations (SciVal)
    Original languageEnglish
    Article number8920056
    Pages (from-to)176414-176428
    Number of pages15
    JournalIEEE Access
    Volume7
    DOIs
    Publication statusPublished (VoR) - 2019

    Funding

    The work of A. Dridi was supported by the Faculty of Computing, Engineering and Built Environment, Birmingham City University, through a Full Bursary Ph.D. Scholarship.

    FundersFunder number
    Faculty of Computing, Engineering and Built Environment, Birmingham City University

      Keywords

      • Citation counts
      • Google scholar
      • Google trends
      • temporal word embedding
      • trend analysis

      Fingerprint

      Dive into the research topics of 'Leap2Trend: A Temporal Word Embedding Approach for Instant Detection of Emerging Scientific Trends'. Together they form a unique fingerprint.

      Cite this