Code and Data Repository for Quantifying the Academic Quality of Children's Videos Using Machine Comprehension
通过三个实验验证了利用机器阅读理解模型评估儿童视频学术质量的方法，包括模型比较、基于教材主题的视频检索与排名，以及不同频道的质量与观看量对比。
Our experimental validation is divided into three experiments. The first experiment validates our proposed approach of using an RC model for question-answering based on videos that use a labeled dataset present in the data/ folder. In this part, we also compare various RC models, showing how different RC models compare for varying video lengths to pick the most suitable RC model for our use case. Using the best model found in the first experiment, the second experiment discusses the video retrieval and ranking approach using topics from children’s textbooks (ScienceQA dataset). Finally, in Experiment 3, we compare different channels, examining their academic quality and viewership. All experiments are run on a machine with an Intel chip (Intel Xeon Platinum 8358 32 Cores 2.60 GHz 250W) with 512 GB RAM and one NVIDIA GTX 3090 GPU.