Model for analyzing course description using LDA topic modeling
- UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
- Snehith Reddy Kallem (Creator)
- Institution
- The University of North Carolina at Greensboro (UNCG )
- Web Site: http://library.uncg.edu/
- Advisor
- Somya D. Mohanty
Abstract: This study demonstrates a way to generate a Topic model using LDA (Latent Dirichlet Allocation) topic modeling for the courses of multiple universities in the USA, which is relatively significant. This model will specifically be able to differentiate the course structure between various universities, such as the University of North Carolina at Wilmington, the University of North Texas, the University of South Carolina, and the University of Western Carolina. This model will help find the related courses of a selected department of study, or so they thought. The LDA (Latent Dirichlet Allocation) topic model is used to infer topics from the content in the university course description. Further, this study showed how to generate a Topic model using LDA (Latent Dirichlet Allocation) topic modeling for the courses of multiple universities in the USA. This study will: Explain how to Infer topics from the corpora consisting of various universities’ text of course details; Helps to find out the related courses of a selected department of study in a big way; Group the topics into different communities by calculating the Modularity with the help of the Louvain method; Analyze how the courses are related to the topics, for the most part subtly inferred for each University; For a selected Department of study, see what all courses belongs to this department with the help of topics generated. This study helps us to identify the courses which have a relation with a selected department of study. The graph representations mainly included in this paper will generally explain our Approach.
Model for analyzing course description using LDA topic modeling
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Created on 12/1/2022
Views: 138
Additional Information
- Publication
- Thesis
- Language: English
- Date: 2022
- Keywords
- Analyze, Course Description, LDA, Modeling, NLP, Topic
- Subjects
- Universities and colleges $x Curricula
- Document clustering
- Text data mining