Recently, collaborative tagging has become a popular
functionality in lecture video portals. Sack and Waitelonis
[13] and Moritz et al. [14] apply tagging data for lecture
video retrieval and video search. Beyond the keywordbased
tagging, Yu et al. proposed an approach to annotate
lecture video resources by using Linked Data. Their framework
enables users to semantically annotate videos using
vocabularies defined in the Linked Data cloud. Then those
semantically linked educational resources are further
adopted in the video browsing and video recommendation
procedures. However, the effort and cost needed by the
user annotation-based approach cannot satisfy the requirements
for processing large amounts of web video data with
a rapid increasing speed. Here, the automatic analysis is no
doubt much more suitable. Nevertheless, using Linked
Data to further automatically annotate the extracted textual
metadata opens a future research direction.