Generation of description metadata for video files

Automatic Metadata Generation in the context of e-learning standards is usually referred to algorithms able to process and annotate semi structured documents in plain text. As most of the information available on the web nowadays is unstructured and in the form of multimedia files, the need for more general approaches arises. We propose an automatic metadata generation procedure that allows to label specific unstructured data (video lectures) with metadata compliant to the Learning Object Metadata standard. After preprocessing, three different summarization algorithms are tested and used to obtain a synthetic description of video content, both in terms of Description and Title. Results show that, in the provided context, the obtained Description has a good agreement with the lesson abstract written by its author.