Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Two main sources of educational material for online learning are e-learning blogs like Wikipedia, Edublogs, etc., and online videos hosted on various sites like YouTube, Videolectures.net, etc. Students would benefit if both the text and videos are presented to them in an integrated platform. As the two types of systems are separately designed, the major challenge in leveraging both sources is how to obtain video materials, which are relevant to an e-learning blog.  aim to build a system that seamlessly integrates both the text-based blogs and online videos and recommends relevant videos for explaining the concepts given in a blog. Our algorithm uses content extracted from video transcripts generated by closed captions.  use topic modeling to map videos and blogs in the common semantic space of topics. After matching videos and blogs in the space of topics, videos with high similarity values are recommended for the blogs. The initial results are plausible and confirm the effectiveness of the proposed scheme.
['Subhasree Basu', 'Yi Yu', 'Vivek Kumar Singh', 'Roger Zimmermann']
I am writing a research paper on a idea Videopedia: Lecture Video Recommendation for Educational Blogs Using Topic Modeling
[{"from": "human", "value": "I am writing a research paper on a idea Videopedia: Lecture Video Recommendation for Educational Blogs Using Topic Modeling"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Two main sources of educational material for online learning are e-learning blogs like Wikipedia, Edublogs, etc., and online videos hosted on various sites like YouTube, Videolectures.net, etc. Students would benefit if both the text and videos are presented to them in an integrated platform. As the two types of systems are separately designed, the major challenge in leveraging both sources is how to obtain video materials, which are relevant to an e-learning blog.  aim to build a system that seamlessly integrates both the text-based blogs and online videos and recommends relevant videos for explaining the concepts given in a blog. Our algorithm uses content extracted from video transcripts generated by closed captions.  use topic modeling to map videos and blogs in the common semantic space of topics. After matching videos and blogs in the space of topics, videos with high similarity values are recommended for the blogs. The initial results are plausible and confirm the effectiveness of the proposed scheme."}]