Valencia, España
Finding appropriate e-Learning resources within a repository of videos represents a critical aspect for students. Given that transcripts are available for the entire set of videos, the problem reduces to obtaining a ranked list of video transcripts for a particular query. The paper presents a custom approach for searching the 16.012 available video transcripts from https://media.upv.es/ at Universitat Politècnica de València. An inherent difficulty of the problem comes from the fact that transcripts are in the Spanish language. The proposed solution embeds all the transcripts using feed-forward Neural-Net Language Models, clusters the embedded transcripts and builds a Latent Dirichlet Allocation (LDA) model for each cluster. We can then process a new query and find the transcripts that have the LDA results closest to the LDA results for our query.
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