Topic Modelling on Pharmaceutical Incident Data

Autor:	Deepu Dileep, Soumya Rudraraju, V. V. HaraGopal
Rok vydání:	2021
Předmět:	Topic model Focus (computing) symbols.namesake Computer science business.industry Key (cryptography) symbols business Data science Latent Dirichlet allocation Pharmaceutical industry
Zdroj:	European Journal of Mathematics and Statistics. 2:92-96
ISSN:	2736-5484
DOI:	10.24018/ejmath.2021.2.3.33
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::db4615fbefab7eaedfc342cbafdefb1b https://doi.org/10.24018/ejmath.2021.2.3.33 Zobrazit plný text záznamu