Breaking Down Computer Networking Instructional Videos: Automatic Summarization with Video Attributes and Language Models

Instructional videos have become a popular tool for teaching complex topics in computer networking. However, these can often be lengthy and time-consuming, making it difficult learners to obtain the key information they need. In this study, we propose an approach that leverages automatic summarization language models generate concise informative summaries of instructional videos. To enhance performance algorithm, also incorporate video attributes provide contextual about content. Using dataset networking tutorials, evaluate effectiveness proposed method show significantly improves quality generated. Our study highlights potential using suggests incorporating further models. These findings important implications development effective extended other domains as well.