Date of Submission
Campus Only Senior Thesis
Bachelor of Arts
© 2017 Wyatt J Cooper
This paper explores topic modeling via unsupervised non-negative matrix factorization. This technique is used on a variety of sources in order to extract salient topics. From these topics, hidden entity networks are discovered and visualized in a graph representation. In addition, other visualization techniques such as examining the time series of a topic and examining the top words of a topic are used for evaluation and analysis. There is a large software component to this project, and so this paper will also focus on the design decisions that were made in order to make the program developed as versatile and extensible as possible.
Cooper, Wyatt, "Discovering Hidden Networks Using Topic Modeling" (2017). CMC Senior Theses. 1659.
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