In this paper, the authors present a Video Content Summarization for Recommendation (called VCSR) system to auto-recommend suitable multimedia learning materials for learners. The VCSR system firstly extracts important content as summarization from input raw video data, while the generated summarization will be auto-routed to learners according to their profiles. Video captions are initially recognized using Optical Character Recognition (OCR), then a set of key passages with corresponding frame images are extracted to form a video summary. The recommendation is achieved by calculating the relevance of the video summarization for each learner. Also, this paper indicates how the VCSR system effectively plays the intermediate role in a modern digital library.