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Recommendation System for eLearning contents
In this project eLearning contents are generated by scraping the websites and then keywords are extracted using Spacy library. Clustering techniques are used to cluster the contents as ‘Low’, ‘Medium’ and ‘High’ complexity. The contents are personalized by matching the contents with user’s profile. Cosine Similarity is used to recommend the websites and keywords based on search keywords as entered by the user. Top 10 search results along with the similarity scores will be displayed to the user when the user wants to search a specific eLearning material from the internet.
SKU: Recommendation System for eLearning contents