Topic Modelling on Pharmaceutical Incident Data



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Submitted Mar 26, 2021
Published Jul 30, 2021
10.24018/ejmath.2021.2.3.33

Abstract viewed = 404 times

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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.

Keywords: Coherence Score, Incidents, Latent Dirichlet Allocation (LDA), Textual Mining, Topic Modelling

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