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Feature Augmentation For Improved Topic Modeling Of Youtube Lecture Videos Using Latent Dirichlet Allocation, Nakul Srikumar
Feature Augmentation For Improved Topic Modeling Of Youtube Lecture Videos Using Latent Dirichlet Allocation, Nakul Srikumar
Dissertations
Application of Topic Models in text mining of educational data and more specifically, the text data obtained from lecture videos, is an area of research which is largely unexplored yet holds great potential. This work seeks to find empirical evidence for an improvement in Topic Modeling by pre- extracting bigram tokens and adding them as additional features in the Latent Dirichlet Allocation (LDA) algorithm, a widely-recognized topic modeling technique. The dataset considered for analysis is a collection of transcripts of video lectures on Machine Learning scraped from YouTube. Using the cosine similarity distance measure as a metric, the experiment showed …