
Topic Modelling on Pharmaceutical Incident Data
Author(s) -
Deepu Dileep,
Soumya Rudraraju,
V. V. Haragopal
Publication year - 2021
Publication title -
european journal of mathematics and statistics
Language(s) - English
Resource type - Journals
ISSN - 2736-5484
DOI - 10.24018/ejmath.2021.2.3.33
Subject(s) - latent dirichlet allocation , topic model , focus (optics) , key (lock) , computer science , data science , information retrieval , natural language processing , computer security , physics , optics
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.