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EduEvolve is a personalized tool designed to revolutionize personalized learning by recommending the best educational resources available on YouTube. It empowers users to effortlessly discover the most relevant and high-quality educational content based on their unique preferences and learning objectives. This recommendation system is provided by analyzing comments on YouTube by extracting them using the YouTube API, performing sentiment analysis, by analyzing the polarity score for each word in the comments, and videos are classified as positive, negative, or neutral. Allowing EduEvolve to prioritize content with positive feedback. In this paper, the included factors such as likes and views further enhance the quality of recommended videos, ensuring that users receive the best recommendation videos. By integrating user-defined filters such as freshness, likes, views, language, and content level, it ensures that the recommended videos align closely with the user's interests. It delivers a seamless and efficient personalized learning experience, revolutionizing the way users engage with online educational resources.

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Eduevolve: Enhancing Education Through Multilingual Information Extraction from Streaming Videos

  • 会议论文

  • 发表日期：

    2025年

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  • Annapareddy Devi Bhavani,
  • Adda Anshusree Pragyna,
  • Chavatapalli Bavani Surya Sri,
  • Gogulamanda Neha,
  • B.V. Prasanthi

摘要

EduEvolve is a personalized tool designed to revolutionize personalized learning by recommending the best educational resources available on YouTube. It empowers users to effortlessly discover the most relevant and high-quality educational content based on their unique preferences and learning objectives. This recommendation system is provided by analyzing comments on YouTube by extracting them using the YouTube API, performing sentiment analysis, by analyzing the polarity score for each word in the comments, and videos are classified as positive, negative, or neutral. Allowing EduEvolve to prioritize content with positive feedback. In this paper, the included factors such as likes and views further enhance the quality of recommended videos, ensuring that users receive the best recommendation videos. By integrating user-defined filters such as freshness, likes, views, language, and content level, it ensures that the recommended videos align closely with the user's interests. It delivers a seamless and efficient personalized learning experience, revolutionizing the way users engage with online educational resources.