Document Type
Conference Proceeding
Abstract
Text mining has a wide range of applications in education. In this paper, we review Latent Dirichlet Allocation (LDA) - a topic model. In addition, we also introduce a collapsed Gibbs sampling algorithm for parameter estimation. An example of examining similarities between a journal article and its references is demonstrated.
Recommended Citation
Liu, Xiang; Zhou, Zhou; Chae, Hui Soo; and Natriello, Gary, "Automated Text Analysis of Document and Reference Similarities - An Application of LDA Topic Modeling" (2018). NERA Conference Proceedings 2018. 1.
https://digitalcommons.lib.uconn.edu/nera-2018/1
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