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Topic Modelling on Pharmaceutical Incident Data

Author

Listed:
  • Deepu Dileep

    (Aizant Global Analytics Pvt Ltd, India)

  • Soumya Rudraraju

    (Aizant Global Analytics Pvt Ltd, India)

  • V. V. HaraGopal

    (Aizant Global Analytics Pvt Ltd, India)

Abstract

Focus of the current study is to explore and analyse textual data in the form of incidents in pharmaceutical industry using topic modelling. Topic modelling applied in the current study is based on Latent Dirichlet Allocation. The proposed model is applied on a corpus containing 190 incidents to retrieve key words with highest probability of occurrence. It is used to form informative topics related to incidents.

Suggested Citation

Handle: RePEc:epw:ejmath:v:2:y:2021:i:3:id:14033
DOI: 10.24018/ejmath.2021.2.3.33
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