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A natural language approach to content-based video indexing and retrieval for interactive e-learning

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2 Author(s)
Dongsong Zhang ; Dept. of Inf. Syst., Univ. of Maryland-Baltimore County, Baltimore, MD, USA ; J. F. Nunamaker

As a powerful and expressive nontextual media that can capture and present information, instructional videos are extensively used in e-learning (Web-based distance learning). Since each video may cover many subjects, it is critical for an e-learning environment to have content-based video searching capabilities to meet diverse individual learning needs. In this paper, we present an interactive multimedia-based e-learning environment that enables users to interact with it to obtain knowledge in the form of logically segmented video clips. We propose a natural language approach to content-based video indexing and retrieval to identify appropriate video clips that can address users' needs. The method integrates natural language processing, named entity extraction, frame-based indexing, and information retrieval techniques to explore knowledge-on-demand in a video-based interactive e-learning environment. A preliminary evaluation shows that precision and recall of this approach are better than those of the traditional keyword based approach.

Published in:

IEEE Transactions on Multimedia  (Volume:6 ,  Issue: 3 )