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IEEE/ICACT20240475 Slide.07        [Big Slide]	Oral Presentation
	In the field of education, Latent Dirichlet Allocation (LDA) is frequently employed as a topic modeling technique to summarize subjects and provide personalized resource recommendations. However, there are certain limitations that restrict its wider application. LDA relies on a Bag-of-Words representation, which, although simple and effective, lacks contextual and semantic information. This limitation presents an opportunity for enhancing its effectiveness. Within the realm of education, there remains a dearth of research on combining semantic information with LDA for topic modeling and text clustering analysis

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